ICLE Comments to FTC Re: Employee Noncompete Agreement RFI

ICLE Comments to FTC Re: Employee Noncompete Agreement RFI

The International Center for Law & Economics (ICLE) appreciates the opportunity to respond to the Federal Trade Commission’s (FTC) Request for Information Regarding Employee Noncompete . . .

The International Center for Law & Economics (ICLE) appreciates the opportunity to respond to the Federal Trade Commission’s (FTC) Request for Information Regarding Employee Noncompete Agreements.[1] We believe the FTC is rightly concerned to identify anticompetitive noncompete agreements “using broadly accepted theories of antitrust harm,”[2] and that it is well within the commission’s authority under the FTC Act to pursue such anticompetitive agreements on a case-by-case basis. We also agree that:

…the Commission’s noncompete enforcement efforts have been obstructed by the Biden-Harris Administration’s Noncompete Rule, a blanket nationwide ban that exceeded the Commission’s regulatory power by purporting to prohibit nearly all noncompete agreements across all industries within the Commission’s jurisdiction without regard for their likely effects in specific contexts.[3]

For those reasons, among others, we support the FTC’s decision to withdraw its notice of appeal in Ryan, LLC v. FTC and to accede to vacate the Noncompete Rule.[4]

Our comments today are brief, although we incorporate by reference additional materials that you will find attached.[5] First, we believe the FTC’s attempted adoption of the Noncompete Rule was an overreach—as today’s commission observes—that rested not just on procedural and statutory errors, but on a slanted and at least somewhat misleading characterization of the FTC’s relevant experience and the relevant economic evidence. For that reason, we attach the comments of ICLE scholars and more than two dozen additional scholars of competition law and economics—including a former FTC general counsel and two former directors of the FTC Bureau of Economics—that we initially submitted to the FTC in response to its notice of proposed rulemaking (NPRM) for the ill-fated Noncompete Rule.[6] In those comments, we explain in some detail why we could not support the rule’s adoption, notwithstanding that “numerous NCAs may be overbroad, inefficient, or otherwise objectionable.” In brief:

First, while the NPRM amply catalogs potential problems associated with non-competes, NCAs, like other vertical restrictions in labor agreements, are not necessarily inefficient, anticompetitive, or harmful to either labor or consumer welfare; they can be efficiency-enhancing and pro-competitive. . . .

Second, and most critically, the emerging body of economic literature regarding the effects of NCAs—or the effects of what is purported to be the relative “enforceability” of NCAs—does not support the categorical ban on NCA usage contemplated by the NPRM. . . .

Third, the Commission has very little experience with NCAs, several very recent settlement agreements notwithstanding. . . .

Fourth, the Commission lacks the resources required for effective enforcement of the Proposed Rule. . . .

Fifth, it is not clear that the Commission has the authority to adopt the Proposed Rule. . . .

Finally, the economic import and the sweep of the Proposed Rule amplify each of the concerns stated above.[7]

Our point about the relevant economic literature may be especially relevant, given the commission’s desire to “better understand the scope, prevalence, and effects of employer noncompete agreements, as well as to gather information to inform possible future enforcement actions.”[8] While the FTC’s noncompete NPRM contains a useful discussion of much of the literature, it is one with significant lacunae and one from which the Biden-era FTC drew questionable conclusions.

Our comments provide an extensive discussion of the relevant literature, including issues and sources that may be unclear in, or simply absent from, the NPRM. That includes, inter alia, research conducted by staff from the FTC’s own Bureau of Economics and other research discussed at the FTC’s 2020 workshop on noncompetes.[9] In fact, most of the literature cited by the Biden-era FTC does not directly address the effects of noncompete agreements but of certain state-law legal changes—chiefly via decisional law—regarding the agreements.

Second, the FTC’s special interest in the use and effects of noncompetes in the health-care sector may well prove fruitful. On the one hand, the economic literature regarding noncompetes in this sector is limited. On the other hand, the commission’s antitrust-enforcement experience in the health-care-provider sector is considerable and built on a solid foundation of research by both FTC and academic economists.[10] That experience and expertise can serve to inform FTC investigations of labor agreements in the sector going forward. It can also help to inform relevant systematic research on health-care-provider noncompetes that might yet be undertaken by Bureau of Economics staff.

A second attachment is a published paper discussing the extant research regarding physician noncompetes.[11] The paper provides an extensive discussion of the relevant findings, and their substantive and methodological limitations. It also sketches conditions under which viable antitrust actions regarding provider noncompetes may lie.

Third, the FTC’s attention to legitimate antitrust issues as they do and might arise in labor markets is commendable. Noncompete agreements and other vertical restrictions in labor markets may well raise competition concerns under established theories of antitrust harm, and according to established analytic methods. Toward that end, an inquiry into genuine anticompetitive exploitation of monopsony power in labor markets may bear procompetitive enforcement fruit.

At the same time, it is important that FTC investigations be mindful of important differences between monopoly and monopsony power, and that they do not give short shrift to both conceptual and empirical challenges posed by the relevant literature. Antitrust has not yet sorted how to deal with such basic questions as, e.g., how to balance directionally opposed effects at different levels of the supply chain or how to handle merger efficiencies in labor-market cases. For those reasons, we attach a relevant paper on labor monopsony and antitrust enforcement.[12]

Finally, there is the old economists’ joke: the plural form of “anecdote” is not “data.” Ad hoc and unverified reports about the terms of particular noncompete agreements and their effects may prove useful to the commission and its staff. They may help to illustrate the variety of noncompetes present in labor markets, as well as concerns that employees and others may have. And certain such reports could well merit follow-up and, potentially, enforcement investigations.

But such reports, however genuinely offered, do not in aggregate provide an adequate sample of the population, whether random or selected. Such reports are not likely to be either comprehensive or balanced in accounting for cognizable harms and benefits associated with (much less caused by) the agreements in question. And such reports are not likely formulated through the lens of either antitrust law, other relevant provisions of the FTC Act, or industrial-organization economics. That is, the reports will provide information—perhaps very useful information—but with an as-yet-unknown signal to noise ratio.

In brief, ad hoc reports submitted to the agency in response to this RFI will not be data. We believe the commission and its expert staff know these limitations, but, equally, should remain mindful of them.

[1] Request for Information Regarding Employee Noncompete Agreements, Docket FTC-2025-0463, Fed. Trade Comm’n (Sep. 4, 2025), https://www.regulations.gov/document/FTC-2025-0463-0001; see also Press Release, Federal Trade Commission Issues Request for Information on Employee Noncompete Agreements, Fed. Trade Comm’n (Sep. 4, 2025), https://www.ftc.gov/news-events/news/press-releases/2025/09/federal-trade-commission-issues-request-information-employee-noncompete-agreements.

[2] Dissenting Statement of Comm’r Melissa Holyoak, In re Non-Compete Clause Rule, Matter No. P201200, Fed. Trade Comm’n (Jun. 28, 2024), at 2.

[3] Id.

[4] Statement of Chairman Andrew N. Ferguson Joined by Commissioner Melissa Holyoak, Ryan, LLC v. FTC, Fed. Trade Comm’n (Sep. 5, 2025), available at https://www.ftc.gov/system/files/ftc_gov/pdf/ferguson-holyoak-statement-re-noncompete-acceding-vacatur.pdf.

[5] These include the following: Comments of Scholars of Law & Economics and the International Center for Law & Economics In the Matter of Non-Compete Clause Rulemaking, Matter No. P201200, Int’l. Ctr. for Law & Econ. (Apr. 19, 2023), available at https://laweconcenter.org/wp-content/uploads/2023/04/ICLE-Noncompete-NPRM-Comments-final.pdf [hereinafter “Comments”]; Daniel J. Gilman, A Competition Perspective on Physician Noncompete Agreements, 61 Inquiry 1 (2024), https://doi.org/10.1177/00469580241237621; Geoffrey A. Manne, Brian C. Albrecht, & Dirk Auer, Labor Monopsony and Antitrust Enforcement: A Cautionary Tale, 74 DePaul L. Rev.1119 (2025).

[6] Comments, supra note 5.

[7] Id. at 3-10.

[8] Request for Information, supra note 1, at 1.

[9] Noncompetes in the Workplace: Examining Antitrust and Consumer Protection Issues, Fed. Trade Comm’n Workshop (Jan. 9, 2020), https://www.ftc.gov/news-events/events/2020/01/non-competes-workplace-examining-antitrust-consumer-protection-issues.

[10] Relevant research by FTC staff and leadership regarding competition among health-care providers includes, inter alia, Devesh Raval et al., Using Disaster Induced Closures to Evaluate Discrete Choice Models of Hospital Demand, 53 RAND J. Econ. 561 (2022); Thomas Koch & Shawn W. Ulrick, Price Effects of a Merger: Evidence from a Physicians’ Market, 59 Econ. Inq. 790 (2021); Keith Brand & Ted Rosenbaum, A Review of the Economic Literature on Cross-Market Healthcare Mergers, 82 Antitrust L.J. 533 (2019); Thomas Koch et al., Physician Market Structure, Patient Outcomes, and Spending: An Examination
of Medicare Beneficiaries, 53 Health Serv. Res. 3549 (2018); Thomas G. Koch, Brett W. Wendling, & Nathan E. Wilson, How Vertical Integration Affects the Quantity and Cost of Care for Medicare Beneficiaries, 52 J. Health Econ. 19 (2017); Julie A. Carlson et al., Economics at the FTC: Physician Acquisitions, Standard Essential Patents, and Accuracy of Credit Reporting, 43 Rev. Indus. Org. 303 (2013); see also, e.g., Martin Gaynor & Robert J. Town, The Impact of Hospital Consolidation—Update, RWJF Synthesis Proj. (2012) (Gaynor is a former director of the FTC Bureau of Economics); Martin Gaynor & William B. Vogt, Competition Among Hospitals, 34 RAND J. Econ. 764 (2003); Maximillian J. Pany, Michael E. Chernew, & Leemore S. Dafny, Regulating Hospital Prices Based on Market Concentration Is Likely to Leave High-Price Hospitals Unaffected, 40 Health Affs. 1386 (Sept. 2021) (Dafny was deputy director for health-care antitrust in the FTC Bureau of Economics from 2012-13); Leemore S. Dafny, Hospital Industry Consolidation—Still More to Come?, 370 New Eng. J. Med. 198 (2014).

[11] Gilman, supra note 5.

[12] Manne, Albrecht, & Auer, supra note 5.

Regulatory Comments

ICLE Comments to the USTR on Significant Foreign Trade Barriers

Executive Summary The International Center for Law & Economics (ICLE) identifies multiple European Union regulatory frameworks that function as significant barriers to U.S. exports of goods and services, and to...

Executive Summary

The International Center for Law & Economics (ICLE) identifies multiple European Union regulatory frameworks that function as significant barriers to U.S. exports of goods and services, and to U.S. foreign direct investment. These measures include the Digital Markets Act, General Data Protection Regulation, Artificial Intelligence Act, the FDI Regulation, and draft regulations on cybersecurity certification and space activities. Each imposes or is likely to impose direct compliance costs on major U.S. technology firms that exceed $100 million annually, with additional indirect costs from foregone innovation, delayed market entry, and reduced investment substantially exceeding this figure.

These regulatory frameworks share common structural features. They impose fixed compliance costs that foreclose market entry for smaller U.S. firms, while raising operational expenses for larger enterprises. They embed vague legal standards that grant enforcement authorities broad discretion, creating uncertainty that deters investment. They also extend regulatory jurisdiction extraterritorially to capture transactions occurring outside EU borders.

Despite formal technological neutrality, these measures disproportionately burden U.S. firms. The Digital Markets Act designates five U.S. companies among seven total “gatekeepers.” The General Data Protection Regulation’s largest enforcement actions target U.S. firms, including a record €1.2 billion fine against Meta. The Artificial Intelligence Act’s penalty structure is based on worldwide turnover, creating disproportionate liability for global U.S. enterprises. The draft Cybersecurity Certification Scheme imposes sovereignty requirements—EU headquarters, EU ownership, immunity from non-EU laws—that U.S. firms cannot meet without divesting ownership or violating U.S. law.

These regulations embed industrial-policy objectives within ostensibly neutral technical standards. EU officials explicitly link the Digital Markets Act to the “digital sovereignty” goals of reducing dependence on non-European technology providers. The FDI Regulation uses security rationales to advance strategic-autonomy objectives. The Cybersecurity Certification Scheme incorporates requirements designed to create protected market segments from which foreign providers are excluded. This approach substitutes political discretion for market-based competition.

Several provisions also constitute forced technology transfer. The Digital Markets Act’s interoperability and data-access obligations compel designated firms to disclose proprietary algorithms and datasets to competitors without meaningful safeguards. Unlike traditional competition remedies that balance access against innovation incentives, these requirements are categorical and unconditional. The asymmetry is deliberate: designated firms must share intellectual property, while they are simultaneously prohibited from using data generated by third parties on their platforms.

The draft Cybersecurity Certification Scheme likely violates EU commitments under World Trade Organization agreements. Sovereignty requirements imposing local-presence mandates and effectively establishing zero quotas for foreign suppliers contravene GATS Articles XVI and XVII on market access and national treatment.

These comments recommend that the Office of the U.S. Trade Representative (USTR) formally designate these measures as significant foreign trade barriers in the 2026 National Trade Estimate Report. Following designation, the USTR should initiate bilateral engagement through the U.S.-EU Trade and Technology Council, with specific negotiating objectives to address the discriminatory provisions. The USTR should raise these barriers in multilateral forums, including the WTO Technical Barriers to Trade and Services Committees.

The United States should not respond through retaliatory tariffs or reciprocal regulatory restrictions. Such measures impose costs on U.S. consumers, harm U.S. firms, and undermine U.S. credibility when advocating for rules-based trade. The appropriate response combines formal trade-barrier designation, sustained diplomatic engagement, and readiness to pursue dispute settlement where violations of international commitments are clear.

I. Introduction

The International Center for Law & Economics (ICLE) thanks the Office of the United States Trade Representative (USTR) for the opportunity to comment on this public consultation on foreign barriers to U.S. exports of goods and services and U.S. foreign direct investment.

ICLE is a nonprofit, nonpartisan research organization whose core mission is to promote the application of law & economics methodologies to inform public-policy discussion. Our scholars have identified multiple foreign policies and practices that deviate from free-trade and free-market principles and that impose measurable costs on U.S. firms seeking to export goods and services, or to make foreign direct investments.

This submission focuses primarily on European Union (“EU”) regulatory measures that function as substantial barriers to U.S. commerce. The Digital Markets Act (DMA), General Data Protection Regulation (GDPR), and Artificial Intelligence Act (AI Act) each impose direct compliance costs on major U.S. technology firms that exceed $100 million annually. In addition to these mandatory expenditures, the measures also subject U.S. firms to indirect costs that substantially exceed this figure from foregone innovation, delayed market entry, and reduced investment.

Beyond digital regulations, our comments examine the EU’s FDI Regulation, which has encouraged the proliferation of national investment-screening mechanisms across EU member states under various security rationales, while serving the industrial-policy objectives of strategic autonomy. We further analyze draft regulations on cybersecurity certification and space activities that impose nationality-based criteria and sovereignty requirements that U.S. firms cannot meet without divesting ownership or violating U.S. law. We also address digital services taxes that multiple jurisdictions have implemented with revenue thresholds designed to capture predominantly U.S. firms. And we examine foreign pharmaceutical-pricing practices that refuse to internalize meaningful portions of innovation costs, while free riding on the benefits of American-funded medical breakthroughs.

These measures share certain common structural features that create non-tariff barriers. They impose fixed compliance costs disproportionate to firm size, effectively foreclosing market entry for U.S. small and medium enterprises. They embed vague legal standards that grant enforcement authorities broad discretion, raising risk premiums that deter investment. They extend regulatory jurisdiction extraterritorially to transactions occurring outside EU borders. They deviate from established international standards through processes that exclude meaningful U.S. participation. They incorporate forced technology-transfer requirements that compel the disclosure of proprietary information to competitors without safeguards against misappropriation.

Despite formal technological neutrality, these frameworks disproportionately burden U.S. firms. The DMA designates five U.S. companies among seven total “gatekeepers” subject to its obligations. The GDPR’s largest enforcement actions target U.S. firms, including a record €1.2 billion fine against Meta for transatlantic data transfers. The AI Act’s penalty structure is based on worldwide turnover, thereby creating disproportionate liability for global U.S. enterprises as compared to EU-focused competitors. The draft Cybersecurity Certification Scheme imposes requirements for EU headquarters, EU ownership, and immunity from non-EU laws that only EU-domiciled firms can satisfy. The draft Space Act establishes size-based constellation thresholds that exempt existing European systems while capturing U.S. large-constellation operators.

The regulations embed industrial-policy objectives within ostensibly neutral technical standards. EU officials have explicitly linked the DMA to the “digital sovereignty” goals of reducing dependence on non-European technology providers. The European Commission has encouraged other jurisdictions, including Brazil, to adopt similar frameworks, extending the reach of EU regulatory protectionism beyond its borders. Multiple countries have implemented or are considering DMA-style asymmetric regulations that target the same U.S. technology firms.

This submission documents these barriers through analysis grounded in economic principles and empirical evidence. Section II examines the DMA’s technical barriers to trade, intellectual-property erosion, services restrictions, investment deterrence, and industrial-policy orientation. Section III analyzes the GDPR’s compliance-cost structure, market distortions, systemic legal uncertainty in transatlantic data transfers, and discriminatory enforcement patterns. Section IV addresses the AI Act’s fixed compliance costs, including market-entry barriers; extraterritorial jurisdiction; technical barriers, which include conformity assessment and prescriptive data requirements; investment deterrence, and regulatory fragmentation. Section V examines the FDI Regulation’s expansion of screening mechanisms, its effects on investment, and its use for industrial-policy objectives. Section VI addresses digital-services taxes. Section VII analyzes foreign pharmaceutical-pricing practices. Section VIII evaluates the draft Cybersecurity Certification Scheme’s evolution toward protectionism, economic inefficiency, specific trade-barrier provisions, and inconsistency with WTO commitments. Section IX addresses the proposed Space Act.

Each section concludes with specific recommendations for USTR action. We recommend formal designation of these measures as significant foreign trade barriers in the 2026 National Trade Estimate Report under the appropriate categories, including Technical Barriers to Trade, Services, Investment, Anticompetitive Practices, and Other Non-Market Policies and Practices. We recommend bilateral engagement through the U.S.-EU Trade and Technology Council with specific negotiating objectives to address discriminatory provisions. We also recommend raising these barriers in multilateral forums, including WTO Technical Barriers to Trade and Services Committees.

The appropriate U.S. response should not involve retaliatory tariffs or similar measures. Such actions would impose costs on American consumers through higher prices and restricted choice, while undermining the global competitiveness of U.S. industries. Instead, we advocate vigorous enforcement of international trade principles, promotion of evidence-based regulation aligned with international standards, and engagement through diplomatic and legal channels to dismantle foreign protectionism. By systematically identifying and challenging these barriers through proper trade policy channels, the USTR can advance the interests of American businesses and workers, while promoting open markets and robust competition in the global economy.

II. Digital Markets Act

The EU’s DMA[1] establishes an expansive regulatory framework governing large online platforms, which it designates as “gatekeepers.” Although formally neutral, the DMA in practice applies almost exclusively to U.S.-headquartered firms that export digital services and invest heavily in Europe’s digital ecosystem. Indeed, five out of the seven firms targeted by the regulation are U.S.-based.[2] By altering the terms of competition and imposing disproportionate compliance costs on a handful of foreign companies, the DMA effectively functions as a non-tariff barrier to trade.[3] It raises the cost of market access, redistributes economic rents toward certain competitors and business users, and restricts the ability (and incentives) of U.S. firms to innovate and invest.[4] In sum, the law’s cumulative effect is likely to disadvantage U.S. exports of digital services and intellectual property, while also deterring U.S. foreign direct investment, in ways inconsistent with the principles of open and nondiscriminatory trade.

A. Technical Barriers to Trade

The DMA introduces an elaborate system of operational and technical obligations that resemble a conformity-assessment regime, which are applied selectively to foreign providers of digital services. Its prescriptive interoperability, data-sharing, and self-preferencing mandates require designated firms to redesign key aspects of their products, interfaces, and internal processes to conform to EU-specific requirements. In practice, designated companies must cooperate and consult the Commission when launching products or making design decisions to ensure that their offerings conform to the Commission’s evolving interpretation of what constitutes “fair” conduct.[5] Indeed, some gatekeepers have observed that “when no two people agree on what the DMA’s substantive obligations mean, the resulting ambiguity undermines the rule of law itself.”[6]

Further, the measures required by the DMA are neither aligned with existing international standards nor with the outcome of transparent, multi-stakeholder processes. By prescribing far-reaching “antitrust-like” obligations and prohibitions absent a finding of market power and without the need to prove harm, the DMA deviates from established antitrust principles, which typically require in-depth case-by-case economic analysis and a clear theory of harm.[7] Instead of adhering to antitrust law’s long-established procedural safeguards and reliance on rigorous economic analysis, the EU has opted to bypass them, using its political and regulatory power to export its policy preferences globally and compel U.S. firms to tailor their products and services “for Brussels.”

The law also embeds an extensive auditing and reporting apparatus that requires firms to produce detailed and costly compliance documentation, appoint an internal compliance officer, submit to technical assessments, and engage in continuous dialogue with the European Commission.[8] These procedures mirror conformity-assessment mechanisms in goods markets and impose compliance costs that fall almost exclusively on U.S. service exporters. Furthermore, U.S. stakeholders and standards organizations have extremely limited influence over the criteria and benchmarks by which “fairness” and “contestability” are assessed, resulting in a process that lacks transparency and inclusivity. As many scholars have pointed out, the terms “fair” and “contestable” are themselves vague and abstract.[9] This ambiguity leaves significant scope for discretion on the Commission’s part, further eroding legal certainty and companies’ freedom to do business however and with whomever they choose.

Collectively, the DMA’s rigid ex-ante requirements function as technical barriers to trade, erecting regulatory hurdles that selectively disadvantage U.S. firms.

B. Intellectual-Property Protection

The DMA’s interoperability and data-access obligations compel designated firms to disclose proprietary information—including technical documentation, algorithms, and datasets—to competitors and third parties. This forced sharing of commercially sensitive materials erodes trade-secret protection and effectively appropriates intellectual property developed by U.S. companies. Unlike traditional competition law, which balances access remedies against innovation incentives,[10] the DMA’s obligations are categorical and unconditional, offering no meaningful safeguards against misuse or loss of proprietary value.

The practical result is a regime of de facto compulsory licensing that weakens incentives to invest in research and development. The DMA thereby undermines the foundational principle that secure intellectual-property rights are essential to innovation. It replaces market discipline with regulatory discretion, transforming proprietary technologies into shared resources, subject to administrative redistribution. Yet the flow of benefits under this regime is entirely one-sided: while the DMA compels designated companies to share data and intellectual property with rivals, it simultaneously prohibits them from using data generated by third parties on their own platforms when competing with those same parties. This asymmetry further weakens their competitive positions and devalues the significant investments that gatekeepers have made in collecting that data and sustaining the platforms on which it is created. Such an approach is inconsistent with international commitments to protect intellectual property, and risks eroding the global value of U.S. innovation.

C. Services

The DMA imposes far-reaching constraints on how U.S. digital-service providers may design, operate, and monetize their offerings within the EU. While the legislation purports to promote “fairness” and “contestability,” its practical effect is to discriminate against foreign suppliers of digital services. The criteria for gatekeeper designation—focusing on global scale and user reach—ensure that almost all targeted firms are American, while “comparable” European companies remain exempt. Indeed, the DMA only applies to one European company, Booking.com.

The obligations themselves restrict the configuration of digital services, including prohibitions on combining data across platforms, limitations on self-preferencing, and mandatory interoperability with third-party software and hardware. These measures directly interfere with platforms’ service design and business models, effectively dictating how U.S. firms may compete and innovate. The DMA also fragments cross-border data flows by compelling firms to maintain separate data-processing structures and by subjecting transatlantic data transfers to heightened compliance risks. This fragmentation functions as a data-localization measure in disguise, impeding the seamless delivery of U.S. cloud, AI, and digital-advertising services across the single market.[11]

Compounding these barriers, the Commission retains broad discretionary authority to interpret and expand DMA obligations through delegated acts and individual enforcement decisions. This open-ended regulatory environment creates substantial uncertainty for U.S. service providers and chills entry and innovation. Together, these features amount to a comprehensive restriction on cross-border trade in digital services, disadvantaging U.S. exporters under the guise of boosting “fairness” and contestability.

D. Investment Deterrence

The DMA deters U.S. foreign direct investment in the European Union. The law likely lowers the expected returns on U.S. capital invested in EU digital markets by constraining profitable business models and imposing unpredictable regulatory costs. For instance, the law’s technology-sharing and data-access obligations constitute a form of forced technology transfer, requiring U.S. investors to surrender valuable intellectual assets as a condition for operating in Europe. Similarly, prohibitions of otherwise standard and often procompetitive business practices, such as favoring a firm’s own products and services,[12] ensure that targeted companies cannot enjoy the full benefits of their investments, including—but not limited to—efficiency-enhancing vertical integration.[13]

At a broader level, the DMA operates as an industrial-policy instrument aimed at advancing the EU’s “digital sovereignty” agenda. Its stated goal of reducing dependence on foreign technology providers translates in practice into the strategic reallocation of rents from globally competitive U.S. firms to European business users and domestic competitors.[14] This policy orientation distorts market incentives and discourages further U.S. investment in the European technology sector. It also risks triggering retaliatory trade measures or reciprocal restrictions on European investment in the United States, further undermining transatlantic economic cooperation.

E. Other Non-Market Policies and Practices: Favoring European Firms and Champions

The DMA exemplifies the EU’s broader shift toward non-market industrial policymaking in the digital sphere. EU officials have openly linked the legislation to Europe’s pursuit of “digital sovereignty”—a policy framework explicitly aimed at reducing reliance on non-European technology providers. The EU has blurred the line between competition policy and protectionism by using regulatory tools to advance industrial and strategic objectives.

This approach distorts global competition by penalizing foreign firms for their success, rather than remedying demonstrable market failures. It undermines commitments to technological neutrality and nondiscrimination under World Trade Organization (WTO) and Organisation for Economic Co-operation and Development (OECD) principles, while signaling to other jurisdictions that digital industrial policy can be pursued through selective regulation, rather than open competition.

Meanwhile, the EU has openly encouraged other countries, such as Brazil, to converge on DMA-style rules.[15] And, sure enough, a number of jurisdictions have already taken note and are following—or considering following—a similar path, targeting the same U.S.-based technology firms with heavy-handed, asymmetric regulations.[16] In this way, the DMA is likely to extend its reach—and the EU’s particular flavor of tech protectionism—well beyond its borders.

F. Recommendations

In substance and effect, the DMA represents a significant foreign trade barrier to U.S. exports of digital services and intellectual property, as well as to U.S. foreign direct investment. While framed as an instrument to foster “fairness” (whatever that may mean), its discriminatory structure, forced technology-transfer obligations, negation of U.S. companies’ legitimate investments efforts, and interference with cross-border data flows reveal a clear industrial policy intent. By selectively burdening U.S. firms under the pretext of promoting “fairness,” the EU has erected a new form of regulatory protectionism in digital markets—and one that is likely to be exported abroad. As such, it imposes restrictions on “Services” (Category 6) and “Investment” (Category 7), and implements “Other Non-Market Policies and Practices” (Category 11) that disadvantage U.S. companies.

The United States should recognize the DMA as a trade measure of concern under the National Trade Estimate process and raise these issues in bilateral and multilateral forums, including the U.S.–EU Trade and Technology Council and the WTO’s Technical Barriers to Trade and Services Committees. Doing so would help to ensure that U.S. firms receive nondiscriminatory treatment and that global digital markets remain open, competitive, and innovation-driven.

III. General Data Protection Regulation

The GDPR is a significant foreign trade barrier that distorts U.S. exports of goods and services and U.S. foreign direct investment. The regulation’s design and enforcement create substantial impediments that fall within several categories enumerated in the USTR’s request for comments.

Under “Services” (Category 6), the GDPR imposes “discriminatory or burdensome barriers to cross-border data flows” and “discriminatory practices affecting trade in digital products.” Its prescriptive rules on data processing and consent create “unreasonable restrictions on what services may be offered,” particularly for U.S. firms whose business models depend on data-driven services. Under “Investments” (Category 7), the GDPR’s high compliance costs, severe financial penalties, and the legal uncertainty surrounding its core provisions deter U.S. foreign direct investment. By increasing operational costs and reducing the expected return on investment, the GDPR discourages U.S. capital from entering the European digital market. In addition, under “Other Barriers” (Category 14), the regulation’s effects are cross-cutting, combining elements of services restrictions, investment deterrence, and anticompetitive market distortions (ACMDs) that justify its inclusion in this category for complex barriers.

The GDPR operates as a formidable non-tariff barrier. The regulation’s real-world economic consequences, the incentive structures it creates, and its effects on market efficiency reveal a system that, regardless of its stated objectives, systematically impedes U.S. commerce. The total economic harm to U.S. interests is estimated to be well in excess of $500 million annually.

A. The GDPR’s Architecture as a Non-Tariff Barrier

A regulation’s compliance costs can function as an implicit tax on economic activity. Notably, Mario Draghi, former president of the European Central Bank and former prime minister of Italy, wrote in the Financial Times:

The IMF estimates that Europe’s internal barriers are equivalent to a tariff of 45 per cent for manufacturing and 110 per cent for services. These effectively shrink the market in which European companies operate: trade across EU countries is less than half the level of trade across US states. And as activity shifts more towards services, their overall drag on growth becomes worse.[17]

When these costs are substantial and disproportionately burdensome on foreign entities, they become a potent non-tariff barrier. The GDPR imposes such a burden on U.S. businesses, creating a financial impediment to operating within the EU market. For example, the Computer & Communications Industry Association estimates the GDPR costs the five largest U.S. providers of online digital services a total of more than $55 million annually.[18]

Beyond these direct outlays, the GDPR imposes indirect costs that reduce productivity and distort resource allocation. A study published by the Centre for Economic Policy Research found that the GDPR caused an average 8.1% drop in profits and a 2.2% decline in sales for affected businesses.[19] The larger effect on profits than on sales indicates that the primary driver of this economic harm is the weight of compliance costs, not a reduction in consumer demand.6

The regulation has also altered the production function for data-driven businesses. A study using seven years of data from a global cloud-computing provider—conducted by researchers that included Mert Demirer of MIT—found that the GDPR effectively increased the cost of data as a production input by approximately 20%.[20] In response, EU-based firms—and U.S. firms serving them—decreased their data storage by 26% and their data processing by 15%. This regulatory friction causes firms to become less data-intensive and, therefore, less efficient. For the United States, whose firms are global leaders in using data for economic value, this functions as a tax on a primary source of competitive advantage.

The GDPR’s “one-size-fits-all” approach, which applies a single set of complex rules regardless of firm size, imposes a regressive burden. The high fixed costs of compliance are disproportionately harmful to smaller U.S. enterprises. Giorgio Presidente and Carl Benedikt Frey found that, behind the 8% average drop in profits, there was a more severe effect for smaller companies. In the IT sector, large firms saw a 4.6% profit drop, while small IT firms suffered a 12.1% drop.[21] This regressive cost structure creates a formidable barrier to entry. U.S. startups and small and medium-sized enterprises (SMEs) must either absorb costs that cripple their profitability or forego the EU market entirely, as noted in Antitrust Source:

Investors, also, may face new uncertainties, information acquisition hurdles, and due diligence costs pertaining to venture deals in the EU due to the introduction of the GDPR. Moreover, those costs may be particularly pronounced for investors who are not based in the EU and are less familiar and less able to monitor ongoing and shifting aspects of compliance and potential enforcement. Investors also face the risks that the value of their investments may diminish if, for instance, an expansion to the EU is put off due to compliance costs, or a funded firm’s assets are less valuable due to limitations on the collection and processing of data.[22]

B. Market Distortions and Disincentives for Innovation

The GDPR’s regulatory design actively distorts the digital economy’s competitive landscape. Its operational requirements create inefficient market outcomes by stifling competition and creating disincentives for innovation. These effects systematically disadvantage the dynamic, data-driven business models in which U.S. firms are global leaders.

The regulation’s rules on data collection—particularly its consent requirements—favor large, established platforms over smaller challengers. Large, vertically integrated platforms with diverse, consumer-facing services are better positioned to obtain broad, bundled user consent across their ecosystems.[23] A user interacting with multiple services from a single provider is more likely to provide sweeping consent than a user interacting with multiple, smaller providers. This dynamic creates a data-collection advantage for incumbents. Empirical research has documented that, in the wake of the GDPR, market concentration increased among web technology vendors, with Google and Meta-owned vendors increasing their relative market share.[24]

Furthermore, large platforms can use the GDPR to justify restricting rivals’ access to data and interoperability, effectively using the regulation as a competitive “weapon.”[25] Such “weaponization” of privacy undermines the contestability of digital markets, harming U.S. firms that often rely on access to platform data to offer complementary services. As John Yun has noted, while the GDPR aims to bolster user privacy, empirical evidence suggests it has also triggered adverse effects, including diminished startup activity and increased market concentration.[26]

The GDPR’s restrictive approach to data processing, combined with its legal ambiguity, acts as a drag on innovation, particularly in data-intensive sectors like artificial intelligence (AI). Economic studies show that venture-capital funding for data-related ventures in the EU fell significantly after the GDPR’s implementation.[27] This lack of investment translates into fewer new companies and less innovation. The regulation’s burdens have also led to market contraction. One study of the Google Play Store found that the GDPR induced the exit of approximately one third of available apps, and that the entry of new apps fell by half following the regulation’s implementation.[28] This signals that the regulatory burden is deterring developers, particularly smaller U.S. software firms, from serving the EU market.

The barriers are particularly acute for the development of AI. Core GDPR principles, such as purpose limitation and data minimization, are in tension with the foundational needs of machine learning, which often requires large, diverse datasets for training.[29] The legal uncertainty surrounding the re-use of data for AI training creates risks for U.S. innovators. Mikołaj Barczentewicz reports that some activists advocate interpreting the GDPR to effectively prohibit some AI research and business applications altogether.[30] Such uncertainty forces firms to either avoid using EU data for training or to adopt overly cautious approaches that limit the effectiveness of their AI models.

C. Systemic Legal Uncertainty in Transatlantic Data Transfers

The GDPR functions as a trade barrier by creating systemic legal uncertainty surrounding the transfer of personal data from the EU to the United States. This chronic instability chills commerce and deters investment.

A series of decisions by the Court of Justice of the European Union (CJEU), stemming from complaints brought by privacy activist Max Schrems, has dismantled the legal architecture for transatlantic data flows. The rulings in Schrems I (2015) and Schrems II (2020) invalidated the “Safe Harbor” and “Privacy Shield” frameworks, respectively.[31] The CJEU’s reasoning in both cases was that U.S. national-security surveillance laws do not provide EU citizens with a level of data protection and judicial redress that is “essentially equivalent” to the rights guaranteed under EU law.

The economic disruption caused by these invalidations was immediate, creating “legal uncertainty for thousands of companies.”[32] U.S. firms were forced to use alternative, more complex transfer mechanisms—primarily Standard Contractual Clauses (SCCs). The Schrems II decision compounded this problem by casting doubt on the validity of SCCs themselves, imposing an obligation on data exporters to conduct a case-by-case assessment of the recipient country’s laws and to implement undefined “supplementary measures.”[33] This created significant operational complexity and regulatory risk for U.S. firms.18

The successor mechanism—the EU-U.S. Data Privacy Framework (DPF), which entered into force in 2023—is built on a precarious legal foundation. Critics argue that the DPF fails to resolve the fundamental conflict between U.S. surveillance law and the CJEU’s “essential equivalence” standard.[34] Legal challenges to the DPF are already underway, and there is a possibility that the framework will be struck down.[35]

This state of perpetual legal jeopardy is a potent economic barrier. The instability of transfer mechanisms raises the risk premium for any U.S. firm doing business with Europe. Companies must invest in continuous legal analysis and contingency planning for the next framework’s collapse, diverting capital from productive activities.[36] The constant threat of a court decision severing data flows makes long-term investment in data-dependent services in the EU an unacceptably risky proposition.

While the EU has not imposed an explicit data-localization mandate, its legal approach creates a powerful de facto incentive for that outcome. For a risk-averse U.S. company, the only safe option is to avoid transferring personal data out of the EU altogether, requiring the construction of duplicative and economically inefficient data infrastructure within the EU’s borders. This outcome is functionally identical to a formal data-localization requirement, a practice recognized by the USTR as a significant barrier to trade in digital services.

D. Discretionary Enforcement and Punitive Sanctions

The final pillar of the GDPR’s architecture as a trade barrier is its enforcement regime. Characterized by vague legal standards, broad regulatory discretion, and punitive sanctions, the regime creates a hostile and uncertain environment for U.S. firms.

The GDPR’s penalty structure has been applied aggressively, with U.S. technology firms the primary targets of the most significant enforcement actions. Since 2018, EU data-protection authorities (DPAs) have issued billions of euros in fines. The record-breaking €1.2 billion fine against Meta in 2023 for its transatlantic data transfers is the largest GDPR fine ever issued.[37] This is part of a pattern that includes a €390 million fine against Meta for its legal basis for advertising and a €310 million fine against LinkedIn. The GDPR empowers authorities to levy fines of up to 4% of a company’s total global annual .[38] This mechanism creates a disproportionate economic threat for large, global U.S. firms, turning any potential compliance issue into a significant financial risk.

Major enforcement actions are frequently based not on clear-cut violations, but on broad, ambiguous principles, granting EU DPAs immense discretion. The €1.2 billion Meta data-transfer fine was based on a violation of Article 46(1) GDPR. The Irish DPA, at the direction of the European Data Protection Board (EDPB), asserted that Meta’s use of SCCs could not overcome the systemic risks posed by U.S. surveillance law. In effect, the decision punished a U.S. company for the perceived shortcomings of the U.S. legal system, a factor outside the company’s control. In the €390 million Meta advertising case, the DPC found that Meta could not rely on “contractual necessity” under Article 6(1)(b) as a legal basis for processing user data for personalized advertising. This decision was contested among EU regulators and overturned the DPC’s own initial view, showing the lack of legal certainty for core business models.[39]

The legal interpretations underlying these actions reflect a regulatory philosophy of “privacy absolutism.” As Mikołaj Barczentewicz has argued, this approach elevates a maximalist interpretation of data protection above other principles, such as economic efficiency and regulatory proportionality.[40] This system, which combines vaguely worded legal principles with the discretionary power to impose massive fines, is ripe for arbitrary enforcement. The evidence shows that this power is disproportionately targeted at high-profile U.S. technology firms, often based on novel interpretations of these vague principles. This transforms the GDPR from a predictable set of rules into a tool that can be wielded to achieve unstated industrial-policy goals, creating a powerful deterrent to U.S. investment and trade.

E. Recommendations

We recommend the USTR formally designate the GDPR as a “Significant Foreign Trade Barrier” in the 2026 National Trade Estimate Report, under the categories of “Services” (Category 6), “Investment” (Category 7), and “Other Non-Market Policies and Practices” (Category 11).

Following this designation, the USTR should initiate high-level engagement with the European Commission to address the specific economic distortions identified. These diplomatic efforts should seek to establish a durable and predictable legal mechanism for EU-U.S. data transfers that can withstand judicial scrutiny and provide the long-term stability needed to support U.S. exports and investment. The USTR should also promote a more risk-based and proportionate approach to GDPR enforcement, advocating for greater legal certainty and nondiscriminatory application of sanctions.

Finally, engagement should address the anticompetitive effects of the GDPR’s design by advocating for interpretations that lower barriers to entry for SMEs and foster a more dynamic and competitive digital single market open to U.S. firms.

IV. Artificial Intelligence Act

The EU’s AI Act constitutes a substantial foreign barrier to U.S. exports of goods and services and U.S. foreign direct investment.[41] This barrier manifests across multiple categories identified in the USTR’s request for comments, including “Technical Barriers to Trade” (Category 2), “Services” (Category 6), Investment (Category 7), and “Anticompetitive Practices” (Category 9).

The AI Act’s regulatory architecture imposes costs on U.S. firms that are substantial in magnitude and poorly calibrated to demonstrated harms. The framework operates through three mechanisms: (1) imposing fixed compliance costs that function as barriers to market entry; (2) creating legal uncertainty that deters investment; and (3) extending EU regulatory jurisdiction extraterritorially to transactions occurring entirely outside EU borders.

A. Fixed Compliance Costs as Market-Entry Barriers

The AI Act requires providers of “high-risk AI systems” to implement extensive compliance infrastructure before placing products on the EU market. Article 9 mandates continuous risk-management systems. Article 10 requires data-governance frameworks that meet specific technical criteria. Article 11 demands detailed technical documentation. Articles 13-15 impose transparency, human-oversight, and technical-performance obligations.

These requirements generate substantial fixed costs that must be incurred regardless of a firm’s EU market scale. The Computer & Communications Industry Association estimates the AI Act will cost large providers of online digital services an average of $15.2 million annually per firm.[42] For small firms, estimates suggest compliance costs of up to €400,000 per high-risk AI system.[43] Other estimates indicate that compliance costs could account for 15-20% of R&D budgets for SMEs.[44]

The European Commission initially projected that 5-15% of AI systems would be classified as high-risk.[45] Recent surveys of AI developers suggest the actual figure is 33-50%.[46] This gap between projected and realized regulatory scope indicates massive underestimation of the act’s economic footprint and trade effects.

Fixed costs create market power by raising minimum efficient scale. For U.S. startups and SMEs, which disproportionately drive AI innovation, these costs would likely exceed expected EU revenue, effectively foreclosing market entry. Large incumbent firms spread compliance costs across larger revenue bases, reducing per-unit costs. While the AI Act includes provisions intended to support SMEs, such as prioritized access to regulatory sandboxes and proportional conformity-assessment fees, these measures are unlikely to offset the immense structural burden of the “high-risk AI systems” (HRAIS) compliance regime. By creating such high hurdles for market entry, the act insulates incumbent EU-based firms from competition from innovative U.S. challengers.

B. Extraterritorial Jurisdiction and Services Trade

Article 2(1)(c) extends the AI Act’s scope to “providers and deployers of AI systems that are located in a third country, where the output produced by the AI system is used in the Union.” This “output-based” jurisdiction represents a significant expansion of regulatory reach that directly restricts U.S. exports of digital services.

A U.S. financial-services firm using a proprietary AI model in New York to generate risk assessments for an EU client becomes subject to EU regulation because the assessment—the “output”—is used in the EU. A U.S. consulting firm using AI tools in Chicago to develop strategy recommendations for an EU company faces identical requirements. A U.S. software company using AI-powered analytics internally to optimize supply chains that serve EU customers likewise must comply with the act.

This jurisdictional approach transforms ordinary cross-border service provision into a regulated activity. U.S. service exporters face costly choices: develop parallel EU-compliant versions of internal processes, accept legal risk of noncompliance, or exit the EU market. Each option imposes costs. Creating parallel systems eliminates economies of scale. Accepting legal risk increases the cost of capital. Market exit represents foregone revenue.

Services represent approximately 35% of total U.S. exports.[47] The European Center for International Political Economy reports that U.S. exports of information and communications technology (ICT) services to the EU have exceeded $220 billion in recent years.[48] The AI Act’s extraterritorial reach subjects significant portions of these services exports to novel compliance requirements and legal risks.

C. Technical Barriers to Trade

The AI Act establishes a significant set of technical barriers that will disproportionately affect U.S. firms. The regulation creates a costly, restrictive framework for U.S. AI exporters through its provisions on conformity assessment, standards development, and data governance.

1. Conformity assessment as gatekeeping

Articles 43 and Annexes VI-VII establish conformity-assessment regimes that AI system providers must complete before placing products on the EU market. For certain high-risk systems, assessment requires the involvement of third-party “notified bodies” designated by EU member states.

This ex-ante requirement delays market entry and imposes costs disproportionate to any feasible risk-reduction benefits. The WTO Technical Barriers to Trade Agreement, Article 5.1.2, requires that conformity-assessment procedures “not be stricter than necessary.”[49] The AI Act’s framework inverts this standard by applying uniform, stringent assessment requirements based on system classification, rather than actual risk.

Delays to market entry translate directly into foregone revenue. In technology markets characterized by rapid obsolescence and network effects, delay often determines market success. A U.S. firm spending six months navigating conformity assessment while competitors launch immediately faces more than lost sales—it may lose the market permanently if competitors establish network effects during that period.

2. Harmonized standards and procedural exclusion

Article 40 directs the European Commission to request European standardization organizations (ESOs)—specifically, the European Committee for Standardization (CEN), the European Committee for Electrotechnical Standardization (CENELEC), and the European Telecommunications Standards Institute (ETSI)—to develop “harmonized standards” for AI systems. Article 41 grants “presumption of conformity” to AI systems that comply with these standards, creating powerful incentives for adherence.

ESOs develop standards through technical committees composed of experts nominated by EU member states’ national standards bodies. While international standards organizations like the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC) include U.S. representatives with voting rights, the ESO process provides no such direct participation to non-EU stakeholders. U.S. firms and U.S.-based standards-development organizations (SDOs) may observe or comment but cannot vote on the adoption of standards.

This procedural structure creates the risk of standards-based protectionism. Standards that appear neutral can advantage domestic producers if they codify approaches or technical architectures common in one market but not another. A harmonized standard specifying particular data structures, software architectures, or testing methodologies familiar to EU developers but foreign to U.S. developers imposes differential compliance costs that advantage EU firms without explicit discrimination.

3. Prescriptive data requirements

Article 10 of the AI Act requires that training, validation, and testing datasets be “relevant, sufficiently representative, and to the best extent possible, free of errors and complete.” These requirements are not performance standards, which would allow firms to choose optimal compliance methods. They are, instead, input mandates that specify the characteristics of data that may be used in development.

The requirements are vague, subjective, and unrealistic, restricting access to usable data and slowing product development. The act’s goal of eliminating bias completely has been deemed technologically unattainable, even for leading AI firms.[50] Additionally, extensive logging and traceability mandates increase compliance costs, privacy risks, and operational complexity, particularly given the opaque nature of large language models (LLMs). U.S. firms have pioneered novel approaches to bias mitigation or data efficiency that do not conform to Article 10’s prescriptive requirements and therefore face regulatory barriers, regardless of their technical merit.

D. Investment Deterrence

A U.S. firm considering whether to establish an AI development facility in the EU must compare expected returns to alternative investment locations. The AI Act raises the costs of EU operations through required risk-management systems, data-governance infrastructure, documentation processes, and conformity assessments. All these costs are specific to EU operations. A firm conducting identical AI research in the United States, Japan, or other jurisdictions faces no comparable burden. At a 10% discount rate, the estimated $15.2 million annual compliance cost has a present value of $152 million—potentially three times an initial capital investment. This dramatically reduces investment returns and causes capital to flow elsewhere. That’s because investment decisions under uncertainty create option value for delay. When regulatory uncertainty is high, the option value of waiting increases, causing firms to delay or abandon investments, even when the expected net present value is positive.[51]

The AI Act creates multiple sources of legal uncertainty. The definition of “high-risk” systems depends on Annex III categories that are broad and subject to updating through delegated acts. Whether specific AI systems qualify as “general purpose AI,” thereby triggering additional requirements under Articles 51-56, depends on assessments of “significant impact” that will be refined through not-yet-adopted implementing regulations. The liability regime for AI-caused harm remains unresolved following the European Commission’s withdrawal of its proposed AI Liability Directive in October 2024.

Article 99 establishes administrative fines for noncompliance. Placing prohibited AI systems on the EU market triggers fines of up to €35 million, or 7% of total worldwide annual turnover, whichever is higher. For large U.S. technology firms with annual revenues that exceed $100 billion, the 7% turnover penalty represents potential liability of more than $7 billion per violation.

This penalty structure creates asymmetry between U.S. and EU firms. The “worldwide turnover” basis means large U.S. firms with substantial global operations face far larger absolute penalties than EU firms of comparable size operating primarily within Europe. This differential penalty burden advantages EU-headquartered competitors.

E. Regulatory Fragmentation

The AI Act represents an attempt to exercise what Anu Bradford of Columbia Law School has termed the “Brussels Effect”—the EU’s strategy of leveraging its large internal market to set de facto global regulatory standards.[52] This effect is failing with respect to AI regulation. The United Kingdom, Japan, Singapore, and the United States have explicitly rejected the EU’s prescriptive, rights-based approach in favor of alternative models that emphasize flexibility, sectoral regulation, and voluntary frameworks.

This regulatory divergence creates trade barriers through fragmentation. U.S. firms seeking to operate globally must develop and maintain compliance systems for multiple, inconsistent regulatory regimes. Rather than creating a unified global standard that reduces compliance costs through harmonization, the Act is producing a fragmented regulatory landscape that multiplies compliance costs and creates barriers to international commerce.

F. Quantifying the Trade Barrier

The available evidence suggests the AI Act’s impact on U.S. exports likely falls into USTR’s highest category: more than $500 million annually. This estimate derives from multiple components. Direct compliance costs for at least 30 major U.S. technology companies with substantial EU AI business exceed $450 million annually. Foregone revenue from delayed launches of Apple Intelligence, Google Gemini, and Meta AI features represents additional hundreds of millions. Lost sales from market exit by smaller U.S. firms, reduced foreign direct investment, and suppressed innovation all compound these effects.

G. Recommendations

The USTR should formally identify the EU AI Act in the 2026 National Trade Estimate Report as a significant foreign barrier affecting U.S. exports and investment under Categories 2, 6, 7, and 9.

The United States should pursue bilateral engagement through the U.S.-EU Trade and Technology Council with specific objectives: (1) negotiate mutual recognition of conformity assessments conducted according to U.S. standards, particularly the National Institute of Standards and Technology (NIST) AI Risk Management Framework procedures; (2) secure direct voting rights for U.S. stakeholders in ESO technical committees developing harmonized standards; (3) urge modification of Article 2(1)(c) to limit extraterritorial jurisdiction to AI systems specifically targeted at the EU market; and (4) advocate for revising prescriptive requirements like Article 10 to performance-based standards that specify outcomes, rather than processes.

These recommendations aim to reduce trade friction while respecting legitimate regulatory objectives concerning AI safety and security.

V. Foreign Ownership Regulations

Regulation (EU) 2019/452, establishing a framework for screening foreign direct investment into the European Union (FDI Regulation),[53] was adopted under the stated objective of protecting “security and public order.” In practice, however, it institutionalizes a permanent mechanism for political intervention in cross-border capital allocation, embedding the logic of “strategic autonomy” into what had previously been an open and integrated internal market.

To be clear, the FDI Regulation does not create a centralized EU screening authority. Instead, it establishes a cooperation mechanism through which the European Commission and member states exchange information and issue nonbinding opinions on individual transactions. Formally, member states retain full sovereignty over whether to screen investments and how to conduct such reviews. Yet the regulation’s design and subsequent implementation have had profound and unintended consequences: it has encouraged the proliferation and expansion of national screening mechanisms, extended the scope of “security” into broad categories of technology and infrastructure, and thereby raised the transaction costs and uncertainty surrounding U.S. investment in the EU.

Ultimately, the framework functions less as a narrow national-security safeguard than as a structural non-tariff barrier to investment—one that distorts market signals, amplifies bureaucratic discretion, and provides a convenient channel for industrial-policy objectives under the guise of “security.”

A. De Facto Expansion of Screening Mechanisms

The FDI Regulation creates an EU-level process for coordinating member-state screening mechanisms but does not harmonize substantive criteria. Member states “may maintain, amend or adopt mechanisms to screen foreign direct investments,” and the Regulation lists a non-exhaustive set of factors—such as control of critical infrastructure, access to sensitive information, or involvement in projects of EU interest—that may justify intervention.[54]

While the regulation is formally voluntary, its cooperative structure and reporting obligations have functioned as a strong incentive for adoption. Member states that lack screening regimes cannot meaningfully participate in the information-exchange process or respond to Commission inquiries. Once several large member states—notably Germany, France, and Italy—began operating comprehensive systems, others faced reputational and administrative pressure to follow suit, lest they be viewed as weak links in the EU’s economic-security chain.[55] This dynamic illustrates collective-action and path-dependence effects familiar in regulatory economics: once a coordination mechanism exists, the marginal political cost of adopting a regime falls, while the cost of abstention rises.

The result has been a near-complete diffusion of screening mechanisms across the EU. In 2018, only about a dozen member states maintained such regimes; by 2025, 26 of 27 had either adopted or substantially expanded them.[56] A procedural framework thus evolved into a de facto mandatory system, extending to sectors only tangentially related to national security, and imposing new layers of uncertainty and delay on cross-border investment.

B. Effects on Investment

By de facto replacing predictable, rules-based market access with open-ended administrative discretion, the FDI Regulation increases both the fixed and variable costs of foreign investment. Because “security or public order” is undefined, and varies from EU member state to member state, investors must evaluate potential exposure across 27 distinct national systems, each with different triggers, thresholds, and timelines. The expected value of an investment falls as both the probability and variance of regulatory delay rise. In effect, the regulation imposes an implicit entry tax on foreign investment, particularly in capital-intensive and time-sensitive sectors, where delay can destroy value.

Moreover, the extension of screening to technology and data-related sectors could create distortions in research collaboration and access to innovation funding. While evidence remains limited regarding the direct application of FDI screening to joint research ventures, the FDI Regulation’s scope explicitly extends to investments that involve EU projects and programs of “Union interest,” such as Horizon Europe.[57] This raises a credible risk that screening mechanisms could be used to scrutinize or constrain foreign participation in collaborative R&D initiatives. The possibility that foreign partners—particularly U.S. firms—might be subjected to review or additional administrative conditions introduces uncertainty and may discourage engagement in EU-funded research consortia.

The FDI Regulation also allows authorities to reexamine previously approved investments if new “security concerns” arise, creating an option for ex-post intervention that investors must price into their discount rates. This regulatory-risk premium raises the cost of capital, deters reinvestment, and diverts resources toward jurisdictions where the expected value of government noninterference is higher.

C. Non-Market Policies and Practices

The FDI Regulation’s implementation demonstrates how security rationales can be repurposed for industrial policy. EU institutions increasingly describe FDI screening as a tool to reduce “strategic dependencies” and, implicitly, to foster European champions.[58] This represents a shift from a market-based framework for capital allocation to one in which political discretion determines ownership patterns in key sectors. Such policies substitute bureaucratic decision making for market discovery, inviting rent seeking and protectionism and reducing consumer welfare.

Despite formal neutrality, the FDI Regulation has disproportionately affected U.S. investors. The European Commission’s own reporting suggests that most screened transactions in 2023 likely involve U.S. acquirers, given that the United States is the primary foreign investor in the EU and given that the United States accounted for 49% of total investments in semiconductors (an area considered sensitive).[59]

D. Caveats

To be sure, the FDI Regulation also incorporates several constructive elements. Prior to its adoption, member-state regimes were highly fragmented—varying widely in scope, procedure, and transparency. The regulation represents a step toward greater institutional coherence, introducing minimum procedural guarantees—such as transparency obligations, defined timelines, and access to judicial review—that help to reduce some of the transaction costs and legal uncertainty associated with purely national systems.[60] It also provides investors with a baseline degree of predictability by clarifying notification processes and information-exchange requirements across jurisdictions.

Moreover, the European Commission has recognized that excessive divergence among national mechanisms can itself act as a barrier to investment and has therefore announced plans to further harmonize screening rules within the union.[61] While these developments modestly improve legal certainty and procedural fairness, they also underscore the underlying tension of the EU’s current approach: the pursuit of uniformity and “strategic autonomy” simultaneously expands the administrative perimeter of investment control.

Paradoxically, therefore, the FDI Regulation seeks to manage the fallout of regulatory fragmentation that arises, to a significant degree, from its own existence. By effectively nudging member states to adopt FDI-screening mechanisms—while leaving the substance of screening in national hands—it is likely to engender a multiplicity of divergent rules and standards, potentially exacerbating legal uncertainty and discouraging investment by foreign firms, the majority of which are U.S.-based.

E. Recommendations

Though nominally adopted to protect “security and public order,” the FDI Regulation has, in practice, spurred the proliferation and expansion of national-screening mechanisms across nearly all EU member states. This dynamic functions as a structural non-tariff barrier, replacing rules-based market access with administrative discretion, which in turn raises transaction costs and creates significant regulatory uncertainty for U.S. investors. The USTR should therefore regard the framework as a potential non-tariff barrier to investment under “Investment” (Category 7) and “Other Non-Market Policies and Practices” (Category 11), as it uses “security” as a guise for industrial-policy objectives that distort market signals and deter U.S. capital. To mitigate its distortive effects, the USTR should:

  1. Urge the EU to encourage member states to narrow their definitions of “security and public order” to objectively verifiable and relatively uniform risks to defense, intelligence, or critical infrastructure.
  2. Advocate for binding procedural disciplines—clear timelines, transparency, and proportionality—to reduce uncertainty and limit rent seeking.
  3. Encourage differentiation between market-based and state-directed investors so that scrutiny targets genuinely nonmarket acquisitions, rather than U.S. commercial investment.
  4. Promote dialogue on proportionality and due process in FDI review to ensure that legitimate security objectives are pursued through narrowly tailored, evidence-based measures.

Member states properly retain the sovereign authority to screen foreign direct investment where genuine national-security interests are implicated. To the extent that the FDI Regulation establishes minimum standards of transparency, legal certainty, and procedural safeguards, it moves in the right direction. Nonetheless, the regulation has also catalyzed the proliferation of national screening mechanisms. Because competence over screening remains decentralized, and because member states continue to define “public order” and “security” according to their own policy preferences, the framework risks entrenching a fragmented and unpredictable regulatory landscape that deters efficient cross-border investment.

VI. Digital Services Taxes (DSTs)

Digital services taxes (DSTs) represent another significant and growing non-tariff trade barrier that disproportionately targets U.S. firms operating in the global digital economy. This barrier may be categorized within the “Other Barriers” category (Category 14) on the USTR’s request for comments.

DSTs are typically structured as a percentage of gross revenue derived from specific digital activities, rather than profits, rendering them highly discriminatory and economically distortive. They often fall most heavily on large, profitable U.S.-based technology companies, fostering an uneven playing field and shifting the cost of compliance and operation back to the origin country of innovation.

A core flaw of DSTs is their inherent bias against foreign (particularly U.S.) digital-service providers. Many DSTs are designed with revenue thresholds that effectively exempt domestic (and typically smaller) players, while capturing only the largest multinational corporations, which are predominantly American. This selective application creates an unfair competitive advantage for local firms and disincentivizes foreign investment. For example, a 2019 report highlighted how European DSTs, despite their broad rhetoric, would disproportionately affect U.S. companies due to their global scale and reliance on digital advertising and user data.[62]

Furthermore, DSTs contribute to significant economic inefficiencies and double taxation. By taxing gross revenue, rather than profits, DSTs fail to account for a given firm’s actual profitability or expenses, potentially imposing tax burdens even on firms operating at a loss. As early as 2018, the European Economic and Social Committee (EESC) expressed apprehension regarding the potential for adverse effects on smaller economies and nascent businesses, along with the heightened risk of double taxation.[63]

This departure from long-standing international tax principles creates overlapping tax claims and discourages investment in the digital sector. The lack of a harmonized international approach compels firms to navigate a complex patchwork of varying tax regimes and growing compliance costs and administrative burdens, as detailed by a PricewaterhouseCoopers analysis of the global landscape of DSTs.[64]

The unilateral implementation of DSTs also fundamentally undermines efforts toward a stable and predictable global tax framework. Despite ongoing multilateral efforts at the OECD to establish a consensus-based solution for taxing the digital economy (such as Pillars One and Two), several countries have proceeded with or maintained their own DSTs. This fragmentation risks trade retaliation (exemplified by U.S. Section 301 investigations into various DSTs), which threaten to escalate trade disputes and harm global economic cooperation.[65] As such, DSTs are not merely a revenue-raising tool but a protectionist measure that obstructs the free flow of digital services and capital, ultimately to the detriment of consumers and innovation worldwide.

VII. Pharmaceutical Pricing

ICLE has previously submitted comments to the USTR regarding foreign pharmaceutical-pricing practices that distort trade and erode U.S. firms’ incentives to innovate and shift the financial burden of pharmaceutical innovation disproportionately onto U.S. consumers.[66] This barrier may fit in the “Other Barriers” (Category 14) of the USTR’s request for comments.

Centralized-negotiation systems are a primary mechanism that foreign governments use to distort pharmaceutical pricing.[67] Nations operating national-health-care or single-payer models leverage their substantial buying power to negotiate or impose stringent price limits on medications.[68] Such centralized systems effectively establish monopsony conditions, confronting pharmaceutical companies with a single buyer that possesses overwhelming market power, and thereby eliminating competitive-pricing dynamics.

Biased health-technology assessments (HTAs) are another mechanism that suppress value-based prices abroad. In Germany, for instance, the Federal Joint Committee (G-BA) routinely refuses to recognize key surrogate or intermediate endpoints—such as progression-free survival or HbA1c—unless sponsors meet exceptionally strict criteria.[69] The United Kingdom’s National Institute for Health and Clinical Excellence (NICE) has maintained its £20k-£30k per “quality adjusted life year” threshold since 1999, despite cumulative UK inflation of approximately 90%.[70] Similarly, France’s Comité Économique des Produits de Santé routinely links new drugs to five-year volume contracts.[71] Once in-market sales reach the agreed cap, manufacturers face mandatory clawbacks that can range from 50–70% of “excess revenue.”[72] Moreover, these agencies often discount future health gains, thereby underweighting the decades-long cumulative benefits of curative or disease-modifying therapies.[73]

External-reference pricing (ERP) systems compound these distortions by systematically benchmarking pharmaceutical prices to suppress market values. These systems ensure foreign drug prices remain artificially low—significantly below what would naturally emerge under competitive market conditions.[74] For instance, Canada’s 2022 shift to the Patented Medicine Prices Review Board (PMPRB11) basket deliberately excluded the United States and Switzerland—its two highest-price peers—substituting them with six mid-priced OECD countries.[75] The Canadian Parliamentary Budget Officer estimates that adopting this slimmer benchmark would have reduced Canada’s 2018 spending on patented drugs by approximately 19%.[76]

South Korea’s “two-waiver” pathway presents an even more stark example: a drug must first be priced below the lowest figure among the A7 high-income comparators (which includes the United States). The subsequent National Health Insurance Service (NHIS) negotiation then references “OECD countries other than A7,” explicitly omitting U.S. prices and locking Korean ceilings well below other advanced-economy levels.[77] Such ERP creates a “race to the bottom” effect, where artificially suppressed prices in one jurisdiction become the ceiling for pricing in others, further entrenching below-market pricing globally

Though foreign governments may claim legitimate cost-containment objectives, pricing systems that refuse to internalize any meaningful portion of innovation costs, while free riding on the benefits of U.S.-funded medical breakthroughs, constitute a massive scheme of industrial policy and subsidization. Indeed, in effect, the entire financial burden of global pharmaceutical development is shifted to U.S. patients.

The key test for distinguishing legitimate regulation from trade distortion would be to focus on whether pricing policies create barriers to U.S. market access and fair competition that extend beyond legitimate regulatory objectives. Typically, these policies constitute ACMDs that systematically prevent U.S. pharmaceutical companies from competing on equal terms, shift competitive burdens disproportionately to foreign markets, or create artificial advantages for domestic competitors.

Addressing foreign pharmaceutical-pricing distortions requires surgical trade-policy responses that target specific discriminatory practices, while preserving the innovation ecosystem that benefits U.S. and global health outcomes. The path forward requires rejecting not only counterproductive retaliation but also counterproductive domestic policies, and to instead pursue targeted international remedies. Rejecting most-favored nation (MFN) pricing for Medicaid, for instance, represents a critical policy imperative to avoid importing foreign distortions into the U.S. market. Implementing MFN pricing that benchmarks U.S. reimbursement rates to foreign prices would significantly undermine revenue streams critical to funding ongoing innovation. This would risk replication of Europe’s historical experience, where similar policies transformed the continent from the global leader in pharmaceutical innovation in the 1970s to its current marginal role.

Instead, policymakers should target specific distortions through calibrated trade remedies, including ACMD tariffication, bilateral negotiations with binding enforcement mechanisms, and multilateral coordination that addresses documented competitive harms without disrupting beneficial trade relationships.

VIII. Draft Cybersecurity Rules

The European Union’s (EU) proposed Cybersecurity Certification Scheme for Cloud Services (EUCS) is a proposed regulatory instrument currently under development that purports to harmonize technical security standards for cloud computing across the EU’s Digital Single Market. The scheme, in development by the European Union Agency for Cybersecurity (ENISA) under the authority of the 2019 EU Cybersecurity Act,[78] has progressively incorporated non-technical, nationality-based criteria that function as significant barriers to U.S. exports of goods and services and U.S. foreign direct investment.[79] These provisions, often grouped under the political objective of achieving “digital sovereignty,” repurpose a technical certification framework into a tool of industrial policy designed to alter market outcomes in favor of domestic European firms.[80]

ICLE scholars have previously cautioned that this conflation of security with protectionism risks erecting digital barriers between the EU and its democratic allies, including the United States.[81] The requirements for data localization, EU-based corporate headquarters and ownership, and immunity from non-EU laws are overtly discriminatory. They create substantial hurdles for U.S. firms, which currently hold a dominant share of the EU cloud market, and are inconsistent with the EU’s commitments under international trade law.

The EUCS was originally conceived to replace a fragmented landscape of national certification schemes with a unified, EU-wide framework. Early drafts from 2020 and 2021 focused on establishing a baseline of technical security requirements organized around three assurance levels—“basic,” “substantial,” and “high”—which corresponded to the level of risk associated with a cloud service’s intended use.[82] This initial direction was consistent with international standards and industry best practices.

The scheme’s trajectory shifted following a push by the European Commission and a bloc of member states—including France, Italy, and Spain—to embed the political doctrine of “digital sovereignty” into its requirements. This doctrine reflects a stated European objective to reduce technological dependence on non-EU countries and insulate European data from the extraterritorial jurisdiction of foreign laws, such as the U.S. Clarifying Lawful Overseas Use of Data (CLOUD) Act.[83] Consequently, later drafts of the EUCS introduced non-technical criteria modeled on France’s highly restrictive national SecNumCloud regime.[84] These criteria include mandates that, for the highest assurance levels, data must be stored and processed exclusively within the EU; that cloud-service providers must be headquartered and owned by EU entities; and that CSPs must demonstrate immunity from non-EU legal jurisdictions.[85]

This evolution was contentious within the EU. A coalition of more trade-oriented member states—including Denmark, Estonia, Greece, Ireland, the Netherlands, Poland, and Sweden—expressed strong concerns that these requirements were political, did not enhance cybersecurity, and were inserted into a technical standard without proper debate.[86] ENISA itself reportedly did not see the need for such sovereignty requirements, viewing them as insufficiently grounded in genuine cybersecurity needs, but ultimately included them at the European Commission’s request.[87]

While the EUCS is officially designated a “voluntary” scheme,[88] this description is misleading.[89] The EU’s Network and Information Security Directive (NIS2)[90] grants member states and the European Commission authority to mandate the use of certified services for a wide range of “essential” and “important” entities.[91] These entities span critical sectors of the European economy, including finance, health care, and energy—all of which must require cloud services certified at the highest assurance levels.[92] It is at these levels that the most discriminatory sovereignty requirements are concentrated. This regulatory mechanism effectively transforms a nominally voluntary scheme into a tool for market foreclosure, creating a protected submarket from which U.S. providers will be excluded.

A. Economic Inefficiency and Protectionist Consequences

From an economic perspective, the EUCS’ sovereignty requirements would be inefficient and would impose significant costs on the European economy. The policy of data localization, which requires data to be stored and processed within a country’s borders, is fundamentally at odds with the economic model of cloud computing.[93] Cloud services derive their efficiency from economies of scale achieved by pooling computing resources and managing data across a distributed global network. Localization fragments this model, forcing the costly duplication of infrastructure like data centers and specialized personnel in multiple jurisdictions.[94] Studies show that such measures increase costs for businesses, particularly SMEs, which are then passed on to consumers.[95]

By excluding or disadvantaging the world’s leading cloud-service providers, the EUCS will reduce competition and innovation in the European market. The European cloud market is a high-growth sector, valued at $185 billion in 2024 and projected to be nearly $590 billion by 2030.[96] U.S.-based providers such as Amazon Web Services, Microsoft Azure, and Google Cloud collectively hold a market share of approximately 70%.[97] This position was achieved through technological leadership and sustained investment. Indeed, U.S. providers invest more than €10 billion each quarter in European capital expenditure.[98]

In contrast, the market share of European cloud-service provides has fallen from 29% in 2017 to 15% in 2022, where it has remained stagnant.[99] Denying European businesses full access to the most advanced and cost-effective global services limits their choices and forces them to rely on a smaller pool of less competitive domestic providers. This protectionist environment reduces the pressure for local firms to innovate and improve efficiency.

The economic damage of such exclusionary policies is quantifiable. An economic analysis by Matthias Bauer and Philipp Lamprecht calculated that, under a maximalist approach to data localization as promoted by the French government, the EU’s annual GDP could fall by as much as 3.9% within two years of implementation, accounting for lost and forgone cloud capacity and productivity growth.[100] They project annual EU GDP losses ranging from €29 billion to €610 billion, depending on the scope of sectors to which the highest assurance levels are applied.

The EUCS’ sovereignty requirements are also likely to weaken—rather than enhance—cybersecurity. Effective cybersecurity relies on the ability to detect and respond to threats in real time across a global network, sharing threat intelligence across borders and employing a 24/7 operational model. As Peter Swire and his co-authors have detailed, data localization fragments these integrated security systems, creating data silos that are more vulnerable to attack.[101] It prevents European customers from benefiting from the global threat visibility that only hyperscale providers can offer and may force them to use smaller local providers who cannot match the multi-billion-dollar annual security investments of their U.S. counterparts.[102]

B. EUCS Provisions as Specific US Trade Barriers

The sovereignty requirements in the EUCS would function as significant barriers to U.S. trade and investment, aligning with several categories of concern outlined in the USTR’s request for comments.

First, the provisions constitute “Technical Barriers to Trade” (Category 2). As currently drafted, the EUCS would impose “unnecessarily trade restrictive standards” and “technical regulations” that deviate from established international norms, such as the ISO/IEC 27000 series, to impose criteria based on nationality and geography. By mandating data localization, EU corporate headquarters, and EU ownership, the scheme would supplant global, risk-based standards with a bespoke “sovereignty” standard that, by design, only a narrow subset of EU-domiciled firms can meet. This is a misuse of the standards-setting process to achieve industrial-policy goals.

Second, the scheme would erect barriers to “Services” (Category 6). The mandate for a cloud-service provider to have its global headquarters in the EU to qualify for the highest assurance levels is a direct “local-presence requirement.” More restrictive is the requirement for “immunity from non-EU laws,” a standard that is legally impossible for any U.S. company to meet. U.S. firms are subject to U.S. laws, such as the CLOUD Act and the Foreign Intelligence Surveillance Act (FISA),[103] which establish legal processes for government authorities to request data, regardless of where that data is stored globally. A U.S. company cannot certify that it is “immune” to U.S. law without violating that law. This provision creates a legal paradox designed for the express purpose of disqualifying U.S. providers.

Third, the framework creates barriers to “Investment” (Category 7). The sovereignty provisions function as de facto “limitations on foreign equity participation” and can compel “technology transfer requirements.” To comply with the scheme’s highest assurance levels, a U.S. cloud-service provider would likely need to establish legally separate, EU-controlled joint ventures with European partners, thereby limiting foreign equity. Such arrangements often come with the requirement to share sensitive intellectual property and operational knowledge with the local partner, which is a form of forced technology transfer.

C. Inconsistency with WTO Commitments Under GATS

The EUCS’ sovereignty requirements would also place the EU in conflict with its legal commitments under the WTO’s General Agreement on Trade in Services (GATS). The measures violate GATS’ core principles of “National Treatment” and “Market Access.”

GATS Article XVII, the national-treatment obligation, requires each WTO member to accord to the services and service suppliers of any other member “treatment no less favorable than that it accords to its own like services and service suppliers” in sectors where commitments have been made. The EUCS fails this test. Cloud-computing services offered by U.S. and EU providers are “like services.” The EUCS accords “less favorable” treatment to U.S. suppliers by imposing requirements for an EU headquarters or “immunity” from non-EU laws. These criteria modify the conditions of competition to the detriment of U.S. suppliers based on their nationality and legal domicile, not on the quality or security of their service. An EU provider can qualify for the highest assurance levels while a U.S. provider offering an identical or superior service is disqualified, which is a clear violation of the national-treatment obligation.

GATS Article XVI, the market-access obligation, prohibits WTO members from maintaining certain types of market-access limitations, including “limitations on the number of service suppliers.” By making it legally and practically impossible for any non-EU firm to meet the criteria for the highest assurance levels, the EUCS effectively imposes a “zero quota” on foreign participation in that segment of the cloud market. WTO jurisprudence, as established in the U.S.—Gambling case,[104] has found that a complete prohibition on a particular mode of service supply constitutes a zero quota in violation of Article XVI. The EUCS achieves the same result through its discriminatory certification criteria.

The EU would likely be unable to justify these measures under the exceptions available in GATS Article XIV, which permit measures “necessary to protect public morals or to maintain public order.” The term “necessary” in WTO law requires that no less trade-restrictive alternative is reasonably available to achieve the same policy objective. In this case, numerous less restrictive alternatives exist to ensure an elevated level of cloud security, including a focus on robust technical controls, strong encryption standards, and rigorous third-party audits, all of which can be applied on a nondiscriminatory basis. Because these effective, nondiscriminatory alternatives exist, the EUCS’ nationality-based requirements are not “necessary.”

Furthermore, Article XIV requires that such measures not be applied in a manner that constitutes “a disguised restriction on international trade in services.” The protectionist intent and effect of the EUCS’ sovereignty requirements indicate they are a “disguised restriction on trade,” making a defense under Article XIV untenable.

The draft EUCS framework is not a legitimate, risk-based security measure. It is an economically inefficient and legally questionable policy that uses the pretext of cybersecurity to favor domestic firms at the expense of market-leading U.S. service providers. The scheme will raise costs for European consumers, reduce innovation, weaken cybersecurity, and place the EU in violation of its foundational commitments under GATS.

D. Recommendations

The USTR should engage with the European Commission immediately, before the EUCS is finalized, to advocate removing the nationality-based sovereignty requirements from the draft framework. The United States should emphasize that opposition to these provisions does not reflect opposition to rigorous cybersecurity standards but rather concern that geographic and ownership criteria are unrelated to genuine security risk and violate WTO commitments.

The primary objective should be alignment of the scheme with the ISO/IEC 27000 series standards and other established international cybersecurity frameworks that focus on technical security controls—such as encryption, access management, and audit mechanisms—rather than corporate domicile or ownership structure. The United States should propose that, where the EU maintains concerns about foreign government access to data, technical safeguards subject to objective conformity assessments provide superior security outcomes than do nationality-based restrictions. Early engagement offers the opportunity to influence the regulatory design before political commitments harden, and implementation investments are made.

The USTR should make clear that, if the EUCS is adopted with the discriminatory sovereignty requirements intact, the United States will designate the scheme as a significant foreign trade barrier in future National Trade Estimate Reports under “Technical Barriers to Trade” (Category 2), “Services” (Category 6), and “Investment” (Category 7). Such designation would be followed by formally raising concerns in the WTO Technical Barriers to Trade and Services Committees, and potentially by dispute-settlement consultations.

The United States should coordinate with other advanced economies whose cloud-service providers would face similar barriers under the draft scheme. Japan, South Korea, Canada, Australia, and other countries with significant technology sectors share U.S. interests in preventing the adoption of sovereignty-based certification frameworks. Joint representations to EU institutions during the finalization process would carry greater weight than unilateral complaints and may provide political cover for European officials seeking to resist member-state pressure for protectionist provisions.

IX. Draft Space Act

ICLE has submitted comments[105] to the U.S. Departments of State and Commerce in which we conclude that provisions of the proposed EU Space Act[106] would function as non-tariff barriers under WTO principles (Appendix A to these comments):

Our analysis concludes that the EU Space Act functions as a nontariff barrier (NTB) under World Trade Organization principles. In design and effect, it selectively targets U.S. large-constellation operators, imposing compliance burdens that are not proportionate to any demonstrated safety or sustainability benefits. The regulation’s structure and procedural mechanisms—most notably its size-based “giga-constellation” threshold, dual-track registration process, and extraterritorial inspection provisions—create discriminatory market-access barriers. These provisions are likely to harm both U.S. and EU economic welfare, slow the pace of innovation in the sector, and shift market share toward geopolitical competitors whose strategic objectives may run counter to transatlantic security interests.

In light of these findings, we recommend that the U.S. government treat the EU Space Act’s discriminatory provisions as nontariff barriers in trade negotiations with the European Union and, where appropriate, pursue remedies through the WTO Technical Barriers to Trade framework. At a minimum, U.S. policy should press for alignment of the EU Space Act with established international orbital safety standards, including those developed by the International Standards Organization, the Inter-Agency Space Debris Coordination Committee, NASA, and the Federal Communications Commission. Such alignment would reduce the risk of market fragmentation, provide regulatory certainty, and ensure that safety objectives are met without imposing unnecessary and discriminatory costs on foreign operators.

ICLE comments are directly responsive to the USTR’s request, as they specifically identify the proposed EU Space Act as a “significant foreign barrier.” The comments detail how the act creates “discriminatory market-access barriers,” aligning with the USTR’s interest in “Technical Barriers to Trade” (Category 2) and “Services” (Category 6) via “discriminatory licensing requirements or regulatory standards.”

Specific examples provided by ICLE, such as the “size-based ‘giga-constellation’ threshold” designed to exempt EU systems and a “dual-track registration process” that creates conflicts of interest, are precisely the types of distortions the USTR seeks to identify for the 2026 National Trade Estimate Report.

X. Conclusion and Recommendations

Our analysis above demonstrates that a concerning pattern of non-tariff trade barriers is emerging (or worsening, if we consider some longstanding trade barriers) from the European Union’s regulatory landscape, significantly impeding U.S. exports of goods and services and deterring U.S. foreign direct investment. From the DMA’s targeted obligations on U.S. gatekeepers to the GDPR’s restrictive data-processing rules, the EU AI Act’s onerous compliance costs, the EUCS’ protectionist cybersecurity mandates, the EU Space Act’s discriminatory satellite regulations, and EU member states’ pharmaceutical-pricing schemes, these policies collectively create a formidable array of challenges for U.S. firms. The FDI Regulation—officially adopted to protect “security and public order”—has, in practice, spurred highly discretionary and costly screening mechanisms across nearly all EU member states.

Regardless of their stated intent, these measures fundamentally distort market competition, erect regulatory hurdles, weaken intellectual-property protections, and shift the burdens of innovation and compliance disproportionately onto U.S. companies and consumers.

A recurring theme across these barriers is the EU’ embrace of goals like “sovereignty” or “fairness” as justifications for policies that are, in practice, highly protectionist. This approach deliberately blurs the lines between legitimate regulatory objectives and industrial policy, using technical standards, data governance, and investment screening as tools to favor domestic champions and reduce reliance on non-EU (primarily U.S.) technology providers. This institutional bias runs counter to the principles of technological neutrality and nondiscrimination that underpin the multilateral trading system, setting a dangerous precedent that encourages other jurisdictions to adopt similar economically harmful and discriminatory regimes.

The path forward requires a firm commitment to promoting free-trade principles and evidence-based regulation, rather than resorting to retaliatory tariffs that ultimately harm U.S. consumers and the broader U.S. economy. We recommend that the USTR actively engage in bilateral and multilateral fora to challenge these discriminatory practices. This includes advocating for narrowing overly broad definitions of indeterminate legal concepts such as “security” and “public order,” pressing for transparent and predictable regulatory processes, encouraging alignment with established international standards, and promoting policies that genuinely foster innovation and competition, rather than protect incumbents.

By systematically addressing these entrenched non-tariff barriers, the USTR can defend the interests of U.S. businesses and innovators, reinforce the integrity of the global trading system, and ensure that the digital economy and other advanced sectors remain arenas for open competition, innovation, and growth, rather than becoming fragmented by protectionist regulatory empires.

The USTR should formally designate the following measures as significant foreign trade barriers in the 2026 National Trade Estimate Report:

  • Digital Markets Act: List under “Services” (Category 6), “Investment” (Category 7), and “Other Non-Market Policies and Practices” (Category 11). The designation should identify specific provisions that function as barriers, including the gatekeeper-designation criteria that disproportionately capture U.S. firms, forced interoperability and data-sharing obligations that appropriate intellectual property, prohibitions on self-preferencing that restrict service design, and data-processing fragmentation that impedes cross-border delivery.
  • General Data Protection Regulation: List under “Services” (Category 6), “Investment” (Category 7), and “Other Barriers” (Category 14). The designation should emphasize the chronic legal uncertainty surrounding transatlantic data transfers following the Schrems I and Schrems II decisions, the regressive compliance-cost structure that forecloses market entry for U.S. SMEs, discriminatory enforcement patterns targeting U.S. firms for record penalties, and the regulation’s demonstrated effects of raising data costs and reducing business productivity.
  • Artificial Intelligence Act: List under “Technical Barriers to Trade” (Category 2), “Services” (Category 6), “Investment” (Category 7), and “Anticompetitive Practices” (Category 9). The designation should highlight the regulation’s extraterritorial jurisdiction extending to outputs used in the EU, conformity-assessment requirements that delay market entry, prescriptive data-governance mandates that deviate from international standards, exclusion of U.S. stakeholders from European standardization processes, and penalty structure based on worldwide turnover that creates disproportionate liability for global U.S. firms.
  • FDI Regulation: List under “Investment” (Category 7) and “Other Non-Market Policies and Practices” (Category 11). The designation should note the framework’s role in encouraging the proliferation of national screening mechanisms, expansion of “security” definitions to encompass broad technology and infrastructure categories and use as a tool to advance “strategic autonomy” industrial-policy objectives under a national-security pretext.
  • Proposed Cybersecurity Certification Scheme: List under “Technical Barriers to Trade” (Category 2), “Services” (Category 6), and “Investment” (Category 7). The designation should identify the sovereignty requirements that mandate EU headquarters and ownership, immunity from non-EU-law provisions that create legally impossible conditions for U.S. firms, data-localization requirements that fragment cloud-computing efficiency, and mandatory certification for critical sectors that transforms a nominally voluntary framework into a market-foreclosure mechanism.
  • Proposed Space Act: List under “Technical Barriers to Trade” (Category 2) and “Services” (Category 6). The designation should reference size-based constellation thresholds designed to exempt EU operators while capturing U.S. firms, dual-track registration processes creating conflicts of interest, and extraterritorial inspection provisions.

The USTR should pursue bilateral engagement through the U.S.-EU Trade and Technology Council with specific negotiating objectives for each designated barrier.

For the DMA, seek commitments that gatekeeper obligations will be applied only following case-specific findings of market power and demonstrable consumer harm, consistent with established antitrust principles. Negotiate the removal of asymmetric restrictions that compel data sharing, while prohibiting designated firms from using third-party data.

For the GDPR, establish durable transatlantic data-transfer mechanisms incorporating binding commitments that successor frameworks will not be subject to unilateral invalidation. Advocate for enforcement guidelines that establish objective criteria to limit discretion and ensure the nondiscriminatory application of penalties.

For the AI Act, negotiate mutual recognition of conformity assessments conducted according to NIST AI Risk Management Framework procedures. Secure direct voting rights for U.S. stakeholders in European standards organizations’ technical committees. Urge modification of Article 2(1)(c)’s extraterritorial jurisdiction provisions to limit application to AI systems specifically targeted at EU markets. Advocate for converting prescriptive input requirements into performance-based outcome standards.

For the EUCS, demand alignment with ISO/IEC 27000 series international standards and removal of nationality-based sovereignty criteria.

For the Space Act, press for alignment with International Standards Organization, Inter-Agency Space Debris Coordination Committee, NASA, and Federal Communications Commission (FCC) orbital-safety standards.

The USTR should raise these barriers in multilateral forums. File concerns with the Technical Barriers to Trade Committee regarding the AI Act’s conformity-assessment regime, the EUCS’ deviation from international cybersecurity standards, and the Space Act’s discriminatory constellation thresholds. Bring concerns to the Services Committee regarding GDPR data-transfer restrictions, DMA limitations on service design, and EUCS local-presence requirements. Consider requesting WTO dispute-settlement consultations on EUCS provisions that appear to violate GATS Articles XVI and XVII market-access and national-treatment obligations.

The United States should coordinate with like-minded trading partners facing similar barriers. Japan, South Korea, Singapore, Canada, and other advanced economies with significant technology sectors share U.S. interests in preventing proliferation of EU regulatory protectionism. Joint representations carry greater weight than unilateral complaints and reduce the risk that EU regulatory approaches will be adopted as de facto global standards.

The United States should not respond to these barriers through retaliatory tariffs or reciprocal regulatory restrictions. Such measures impose costs on U.S. consumers through higher prices and reduced choice, harm U.S. firms through supply-chain disruption, and undermine U.S. credibility when advocating for open markets and rules-based trade. The appropriate response combines formal trade-barrier designation, sustained bilateral and multilateral diplomatic engagement, and readiness to pursue dispute settlement where violations of international commitments are clear.

These recommendations aim to reduce trade friction and restore competitive neutrality, while respecting legitimate regulatory objectives. Where foreign governments pursue genuine public-interest goals through nondiscriminatory, proportionate, and evidence-based measures aligned with international standards, U.S. trade policy should acknowledge those objectives. Where regulatory frameworks systematically disadvantage U.S. firms through discriminatory design, vague standards that enable arbitrary enforcement, or explicit nationality-based criteria, trade policy should identify those practices as barriers and seek their removal through the appropriate channels.

[1] Regulation (EU) 2022/1925 of the European Parliament and of the Council of 14 September 2022 on Contestable and Fair Markets in the Digital Sector (Digital Markets Act), 2022 O.J. (L 265) 1.

[2] Gatekeepers—Digital Markets Act (DMA), Eur. Comm. (last visited Oct. 29, 2025), https://digital-markets-act.ec.europa.eu/gatekeepers_en.

[3] This has also been recognized by the USTR. See, e.g., 2025 National Trade Estimate Report on Foreign Trade Barriers, Off. U.S. Trade Rep. (Mar. 2025), at 154, available at https://ustr.gov/sites/default/files/files/Press/Reports/2025NTE.pdf. (“The ‘gatekeepers’ designated by the DMA disproportionately capture U.S. firms compared to their EU competitors, and therefore undermine U.S. competitiveness in the European market by increasing the compliance costs on certain U.S. firms while not placing a similar burden on EU competitors. The Commission is currently investigating U.S. firms and has imposed excessive fines for violating the DMA”).

[4] For a more thorough critique of the DMA, see, e.g., Lazar Radic, Geoffrey A. Manne, & Dirk Auer, Regulate for What? A Closer Look at the Rationale and Goals of Digital Competition Regulations, 22 Berkeley Bus. L.J. 1 (2025).

[5] The so-called DMA workshops illustrate the opaque and one-sided dynamics of DMA enforcement, in which companies are expected to anticipate when the Commission will deem a product-design decision “fair” and sufficiently conducive to “contestability.” See DMA Stakeholders Workshops, Digital Markets Act (DMA), Eur. Comm., https://digital-markets-act.ec.europa.eu/events/workshops_en (last visited Oct. 29, 2025).

[6] Mikołaj Barczentewicz, EU DMA Workshops: Google, Amazon, Apple, Meta, and Microsoft, EUTechReg (Jul. 8, 2025), https://eutechreg.com/p/eu-dma-workshops-google-amazon-apple.

[7] See Radic et al., supra note 4, at 213-227.

[8] See Barczentewicz, supra note 7.

[9] Giuseppe Colangelo, In Fairness We (Should Not) Trust: The Duplicity of the EU Competition Policy Mantra in Digital Markets, 68 Antitrust Bull. 669 (2023).

[10] See, e.g., Giuseppe Colangelo, Android Auto: The End of the Essential Facility Doctrine as We Know It, Kluwer Compet. Law Blog (Mar. 13, 2025), https://legalblogs.wolterskluwer.com/competition-blog/android-auto-the-end-of-the-essential-facility-doctrine-as-we-know-it.

[11] See Geoffrey A. Manne, Dirk Auer, Lazar Radic, & Selcukhan Ünekbas, Response of the International Center for Law & Economics: Consultation on the First Review of the Digital Markets Act, Int’l Ctr. Law & Econ. (Sep. 24, 2025), at 8-9 available at https://laweconcenter.org/wp-content/uploads/2025/09/ICLE-DMA-Consultation.pdf. (“An example is the interaction between the DMA and the Data Act, both of which contain data sharing rules. Read together, these measures contribute to what might be described as a policy of data immobility. The Data Act explicitly excludes gatekeepers from benefitting as recipients of data sharing… Even where transfers are permitted, the Data Act imposes a requirement that they be made on fair, reasonable, and non-discriminatory terms, including a prohibition on favourable treatment of affiliated enterprises. This reduces the attractiveness of intrafirm data transfers, effectively constraining data flows even within the same corporate group.”)

[12] For the argument that self-preferencing is not presumptively harmful, see Pablo Ibáñez Colomo, Self-Preferencing: Yet Another Epithet in Need of Limiting Principles, 43 World Compet. (4) 417 (2020). (arguing that self-preferencing is, in fact, a reflection of competition on the merits); see also Lazar Radic & Geoffrey A. Manne, Amazon Italy’s Efficiency Offense, Truth on the Mkt. (Jan. 11, 2022), https://truthonthemarket.com/2022/01/11/amazon-italys-efficiency-offense (arguing that there can be multiple procompetitive reasons why Amazon would choose to give preferential treatment to its own products or services).

[13] On the misguided notion—especially popular among regulators in the context of digital markets—that vertical integration should be presumed anticompetitive, see Geoffrey A. Manne, Against the Vertical Discrimination Presumption, Concurrences No. 2-2020, art. No. 94267 (May 2020), (“The problem, however, is that the claims of presumptive harm from vertical discrimination are based neither on sound economics nor evidence.”).

[14] See Radic et al., supra note 4, 243-249; see also Lazar Radic, Gatekeeping, the DMA, and the Future of Competition Regulation, Truth on the Mkt. (Nov. 8, 2023), https://truthonthemarket.com/2023/11/08/gatekeeping-the-dma-and-the-future-of-competition-regulation (“Prior to the DMA’s adoption, many leading European politicians were touting the text as a protectionist industrial-policy tool that would hinder U.S. firms to the benefit of European rivals. This logic dovetails neatly with the EU’s broader push for ‘technology sovereignty,’ a strategy intended to reduce the continent’s dependence on technologies that originate abroad (even if that means stifling the companies from its biggest ally: the United States).”).

[15] CADE and European Commission Discuss Collaboration on Digital Market Agenda, Conselho Administrativo de Defesa Econômica (Mar. 29, 2023), https://www.gov.br/cade/en/matters/news/cade-and-european-commission-discuss-collaboration-on-digital-market-agenda.

[16] These include Japan, Brazil, Turkey, Australia, India, South Africa, Vietnam, and South Korea, among others. Not all these countries, however, have adopted DMA-like rules. See Radic et al., supra note 4; see also Lazar Radic, Your Definitive End-of-Year Global Tech Regulation Wrap-Up: Who’s Doing What, Where, and What to Make of It, Truth on the Mkt. (Dec. 21, 2022), https://truthonthemarket.com/2022/12/21/your-definitive-end-of-year-global-tech-regulation-wrap-up-whos-doing-what-where-and-what-to-make-of-it.

[17] Mario Draghi, Forget the US—Europe Has Successfully Put Tariffs on Itself, Financ. Times (Feb. 14, 2025), https://www.ft.com/content/13a830ce-071a-477f-864c-e499ce9e6065.

[18] Carl J. Schramm, Costs to U.S. Companies from EU Digital Services Regulation, Comp. & Commcn’s Ind. Ass’n (Jul. 2025), available at https://ccianet.org/wp-content/uploads/2025/07/CCIA_Costs-to-US-Companies-from-EU-Digital-Services-Regulation_finalreport.pdf.

[19] Giorgio Presidente & Carl Benedikt Frey, The GDPR Effect: How Data Privacy Regulation Shaped Firm Performance Globally, VoxEU (Mar. 10, 2022), https://cepr.org/voxeu/columns/gdpr-effect-how-data-privacy-regulation-shaped-firm-performance-globally.

[20] Mert Demirer, Diego J. Jiménez Hernández, Dean Li, & Sida Peng, Data, Privacy Laws and Firm Production: Evidence from the GDPR (NBER Working Paper No. 32146, Dec. 2024), available at https://www.nber.org/system/files/working_papers/w32146/w32146.pdf.

[21] Presidente & Frey, supra note 19.

[22] Jian Jia , Ginger Zhe Jin, & Liad Wagman, The Persisting Effects of the EU General Data Protection Regulation on Technology Venture Investment, Antitrust Source (Jun. 2021), available at https://www.americanbar.org/content/dam/aba/publishing/antitrust-magazine-online/2021/june-2021/jun2021-jia.pdf.

[23] See Damien Geradin, Theano Karanikioti, & Dimitrios Katsifis, GDPR Myopia: How a Well-Intended Regulation Ended Up Favouring Large Online Platforms—the Case of Ad Tech, 17 Eur. Competition J. 47 (2020).

[24] Adam Thierer, GDPR & European Innovation Culture: What the Evidence Shows, Medium (Feb. 5, 2023), https://medium.com/@AdamThierer/gdrp-european-innovation-culture-what-the-economic-evidence-shows-b19d2309de07.

[25] Damien Geradin, Theano Karanikioti, & Dimitrios Katsifis, supra note 23, at 51 (2020) (“[L]arge online platforms are increasingly invoking the GDPR—or privacy concerns more generally—as an excuse to engage in controversial and potentially restrictive practices. This could be referred to as the “weaponization” of the GDPR and privacy.”).

[26] See John Yun, A Report Card on the Impact of Europe’s Privacy Regulation (GDPR) on Digital Markets, 31 Geo. Mason L. Rev. F. 104 (2024).

[27] See, e.g., Garrett Johnson, Economic Research on Privacy Regulation: Lessons from the GDPR and Beyond (NBER Working Paper No. 30705, Dec. 2022), available at https://www.nber.org/system/files/working_papers/w30705/w30705.pdf.

[28] Rebecca Janßen, Reinhold Kesler, Michael E. Kummer, & Joel Waldfogel, GDPR and the Lost Generation of Innovative Apps, (NBER Working Paper No. 30028, May 2022), available at https://www.nber.org/system/files/working_papers/w30028/w30028.pdf.

[29] Mikołaj Barczentewicz, Should the GDPR Prohibit AI?, Truth on the Mkt. (Nov. 5, 2024), https://truthonthemarket.com/2024/11/05/should-the-gdpr-prohibit-ai.

[30] Id.

[31] Maximillian Schrems v. Data Prot. Comm’r, Case C-362/14, ECLI:EU:C:2015:650 (Oct. 6, 2015) (“Shrems I”); Data Prot. Comm’r v. Facebook Ireland Ltd., Case C-311/18, ECLI:EU:C:2020:559 (July 16, 2020) (“Shrems II”).

[32] Frances M. Green, Adequacy of the EU–U.S. Data Privacy Framework Survives Challenge, Epstein Becker Green (Sep. 12, 2025), https://www.workforcebulletin.com/adequacy-of-the-eu-u-s-data-privacy-framework-survives-challenge.

[33] Vanessa Zimmer, Winter Is Here: The Impossibility of Schrems II for U.S.-Based Direct-to-Consumer Companies, 42 Nw. J. Int’l L. & Bus. 75 (2021).

[34] See Sergi Batlle & Arnaud van Waeyenberge, EU-US Data Privacy Framework: A First Legal Assessment, 15 Eur. J. Risk Reg. 191 (2024).

[35] See Mikołaj Barczentewicz, Schrems III: Gauging the Validity of the GDPR Adequacy Decision for the United States, Int’l Ctr. Law & Econ. (Sep. 25, 2023), available at https://laweconcenter.org/wp-content/uploads/2023/09/ICLE-Schrems-III_2023.09.21.pdf.

[36] Ross McKean, John Magee, & Rachel de Souza, DLA Piper GDPR Fines and Data Breach Survey: January 2025, DLA Piper (Jan. 2025), https://www.dlapiper.com/en-us/insights/publications/2025/01/dla-piper-gdpr-fines-and-data-breach-survey-january-2025.

[37] CMR, GDPR Enforcement Tracker (retrieved Oct. 29, 2025), https://www.enforcementtracker.com.

[38] Regulation (EU) 2016/679, art. 83(5), 2016 O.J. (L 119) 1, 28.

[39] Rachel De Souza, EU & Ireland: Meta’s Legal Basis for Targeted Ads Found to Breach GDPR, DLA Piper (Jan. 10,2023), https://privacymatters.dlapiper.com/2023/01/eu-ireland-metas-legal-basis-for-targeted-ads-found-to-breach-gdpr.

[40] Mikołaj Barczentewicz, The EU’s GDPR “Fix” Misses the Point Entirely, Truth on the Mkt. (Jun. 24, 2025), https://truthonthemarket.com/2025/06/24/the-eus-gdpr-fix-misses-the-point-entirely.

[41] Regulation (EU) 2024/1689 of the European Parliament and of the Council of 13 June 2024 on Artificial Intelligence and amending Regulations (EC) No. 300/2008, (EU) No. 167/2013, (EU) No. 168/2013, (EU) 2018/858, (EU) 2018/1139, and (EU) 2019/2144 and Directives 2014/90/EU, (EU) 2016/797, and (EU) 2020/1828, 2024 O.J. (L 206) 1 (EU).

[42] Schramm, supra note 18, at 39.

[43] Benjamin Mueller, How Much Will the Artificial Intelligence Act Cost Europe?, Ctr. for Data Innov. (Jul. 2021), available at https://www2.datainnovation.org/2021-aia-costs.pdf.

[44] Gideon Abako, It’s Too Hard for Small and Medium-Sized Businesses to Comply with the EU AI Act: Here’s What to Do, AI Pol’y Bull. (May 19, 2025), https://www.aipolicybulletin.org/articles/its-too-hard-for-small-and-medium-sized-businesses-to-comply-with-eu-ai-act-heres-what-to-do.

[45] Commission Staff Working Document, Impact Assessment Accompanying the Proposal for a Regulation of the European Parliament and of the Council Laying Down Harmonised Rules on Artificial Intelligence (Artificial Intelligence Act) and Amending Certain Union Legislative Acts, Eur. Comm., SWD (2021) 84 final, at 68 (Apr. 21, 2021), https://ec.europa.eu/newsroom/dae/redirection/document/75792 (“[G]iven that in this option high-risk applications are based on exceptional circumstances, one could estimate that no more than 5% to 15% of all applications should be concerned by the requirements.”).

[46] Andreas Liebl & Till Klein, AI Act Impact: Survey Exploring the Impact of the AI Act on Startups in Europe, Init. for Applied Int’l Intelligence (Dec. 12, 2022), available at https://aai.frb.io/assets/files/AI-Act-Impact-Survey_Report_Dec12.2022.pdf.

[47] USITC Analyzes Market Conditions and Outlook for Professional Services in Annual Services Report, U.S. Int’l Trade Comm’n (Jul. 2, 2025), https://www.usitc.gov/keywords/services-trade.

[48] Matthias Bauer, Dyuti Pandya & Oscar du Roy, Openness as Strength: The Win-Win in EU-US Digital Services Trade, Eur. Ctr. for Int’l Pol. Econ. (Mar. 2024), https://ecipe.org/wp-content/uploads/2024/03/ECI_24_PolicyBrief_05-2024_LY03.pdf.

[49] Agreement on Technical Barriers to Trade, Apr. 15, 1994, Marrakesh Agreement Establishing the World Trade Organization, 1868 U.N.T.S. 120 (1994).

[50] Oliver Roberts, EU AI Act’s Burdensome Regulations Could Impair AI Innovation, Bloomberg Law (Feb. 21, 2025), https://news.bloomberglaw.com/us-law-week/eu-ai-acts-burdensome-regulations-could-impair-ai-innovation.

[51] See, e.g., Kenneth J. Arrow & Anthony C. Fisher, Environmental Preservation, Uncertainty, and Irreversibility, 88 Q. J. Econ. 312 (1974) (explaining that, when a decision is irreversible and future benefits and costs are uncertain, immediate action eliminates the opportunity to learn more before committing resources; by waiting, society retains an “option value,” i.e., the value of preserving flexibility to act later when uncertainty has been reduced).

[52] Anu Bradford, The Brussels Effect: How the European Union Rules the World (2019).

[53] Regulation (EU) 2019/452 of the European Parliament and of the Council of 19 March 2019 establishing a framework for the screening of foreign direct investments into the Union, 2019 O.J. (L 79) 1.

[54] FDI Regulation, Arts. 3-4.

[55] Luis Alonso Cabezas Villagarcia, Foreign Direct Investment in the European Union: A Critical and Comparative Overview, Mondo Internazionale (Feb. 11, 2025), https://mondointernazionale.org/en/focus-allegati/foreign-direct-investment-in-the-european-union-a-critical-and-comparative-overview.

[56] Commission Staff Working Document, Third Annual Report on the Screening of Foreign Direct Investments into the Union, SWD (2024) 281 final (Sep. 11, 2024).

[57] See Investment Screening in the EU, Eur. Comm., https://policy.trade.ec.europa.eu/enforcement-and-protection/investment-screening_en (last visited Oct. 29, 2025); Framework for Screening of Foreign Direct Investment into the European Union, OECD (2022), available at https://www.oecd.org/content/dam/oecd/en/publications/reports/2022/01/framework-for-screening-foreign-direct-investment-into-the-eu_d966075e/f75ec890-en.pdf.

[58] Joint Communication to the European Parliament, the European Council and the Council, European Economic Security Strategy, JOIN (2023) 20 final (Jun. 20, 2023); see also Jorge Valero, 19 EU Countries Call for New Antitrust Rules to Create ‘European Champions’, Euractiv (Dec. 18, 2018), https://www.euractiv.com/news/19-eu-countries-call-for-new-antitrust-rules-to-create-european-champions.

[59] Commission Staff Working Document, Third Annual Report on the Screening of Foreign Direct Investments into the Union, SWD (2024) 281 final (Sep. 11, 2024).

[60] FDI Regulation, Art. 3(2).

[61] See Proposal for a Regulation of the European Parliament and of the Council Amending Regulation (EU) 2019/452, Eur. Comm. (Jul. 3, 2024), COM (2024) 395 final (recognizing “uneven implementation” among member states and proposing greater harmonization); Third Annual Report on the Screening of Foreign Direct Investments into the Union, Eur. Comm. SWD (2024) 281 final (Sep. 11, 2024).

[62] Matthias Bauer, Digital Services Taxes as Barriers to Trade: Case Study, Eur. Ctr. for Int’l Pol. Econ. (Nov. 2019), available at https://ecipe.org/wp-content/uploads/2019/11/CaseStudy_DigitalService.pdf.

[63] Proposal for a Council Directive Laying Down Rules Relating to the Corporate Taxation of a Significant Digital Presence, COM(2018) 147 final – 2018/0072 (CNS); Proposal for a Council Directive on the Common System of a Digital Services Tax on Revenues Resulting from the Provision of Certain Digital Services, Eur. Econ. & Social Commit., COM(2018) 148 final – 2018/0073 (CNS) (Jul. 30, 2018), available at https://data.consilium.europa.eu/doc/document/ST-11484-2018-INIT/en/pdf.

[64] State of Play of Digital Services Taxes (DSTs) and Other Similar Measures, PricewaterhouseCoopers (Aug. 29, 2025), available at https://www.pwc.com/gx/en/tax/newsletters/tax-policy-bulletin/assets/pwc-state-of-play-of-dsts-and-other-similar-measures.pdf.

[65] Id.

[66] Comments of the International Center for Law & Economics, Re: Request for Comments Regarding Foreign Nations Freeloading on American-Financed Innovation, Int’l Ctr. Law & Econ. (Jun. 26, 2025), https://laweconcenter.org/resources/icle-comments-to-ustr-on-pharmaceutical-pricing.

[67] Funding the Global Benefits to Biopharmaceutical Innovation, Counc. Econ. Advis. (2020), at 5, available at https://trumpwhitehouse.archives.gov/wp-content/uploads/2020/02/Funding-the-Global-Benefits-to-Biopharmaceutical-Innovation.pdf.

[68] Id.

[69] German Benefit Assessment—White Paper: Latest Methodological Requirements in the German Benefit Assessment, Eur. Fed. Stat. Pharm. Ind. (May 2025), at 4, 39, available at https://www.efspi.org/wp-content/uploads/2025/05/GermanHTA_WhitePaper_2025.pdf (“’Key surrogate’ and ‘intermediate endpoints’ refer to measurable indicators used in clinical trials to approximate the effect of a treatment on meaningful patient outcomes. Surrogate endpoints (e.g., tumor shrinkage in cancer trials) function as substitutes for direct clinical outcomes (e.g., survival), while intermediate endpoints (e.g., blood pressure reduction or HbA1c levels in diabetes) reflect early changes that may predict long-term benefits. These markers are often used when direct outcomes take years to observe, but their validity for regulatory or reimbursement decisions depends on evidence linking them to patient-relevant effects.”).

[70] Jacoline Bouvy, Should NICE’s Cost-Effectiveness Thresholds Change?, NICE Blogs (Dec. 13, 2024), https://www.nice.org.uk/news/blogs/should-nice-s-cost-effectiveness-thresholds-change; John Appleby, Nancy Devlin, & David Parkin, NICE’s Cost-Effectiveness Threshold, 335 Br. Med. J. 358 (2007), available at https://pmc.ncbi.nlm.nih.gov/articles/PMC1952475/pdf/bmj-335-7616-edit-00358.pdf; As of June 25, 2025, £1 in 1999 is worth £1.92. Current inflation rates can be calculated on the Bank of England’s site. See Inflation and the 2% Target, Bank Eng., available at https://www.bankofengland.co.uk/monetary-policy/inflation (last visited Jun. 25, 2025).

[71] Marc A. Rodwin, What Can the United States Learn from Pharmaceutical Spending Controls in France? (Commonwealth Fund Issue Brief, Nov. 11, 2019), https://www.commonwealthfund.org/publications/issue-briefs/2019/nov/what-can-united-states-learn-drug-spending-controls-france.

[72] Id.

[73] Rick Chapman et al., Value Assessment Methods and Pricing Recommendations for Potential Cures: A Technical Brief, at 13 (Inst. Clin. Econ. Rev., Aug. 6, 2019), available at https://icer.org/wp-content/uploads/2020/10/Valuing-a-Cure-Technical-Brief.pdf.

[74] CEA, supra note 51 at 5-8.

[75] Teresa A. Reguly & Eileen M. McMahon, PMPRB Regulations: New Basket of Comparator Countries Has Arrived, Absent Guidance, Torys (Jul. 7, 2022), https://www.torys.com/en/our-latest-thinking/publications/2022/07/pmprb-regulations.

[76] Canadian Patented Drug Prices: Gauging the Change in Reference Countries, Parliam. Budg. Off. (Jun. 14, 2022), https://distribution-a617274656661637473.pbo-dpb.ca/1135d8aba4de3c35a1098e80fd5209fddb097920d354f8ac79ec3b1cf8918ff5.

[77] Seung-Rae Yu, Improving the Reimbursement Process for New Drugs: A Case Study of a Two-Waiver System in South Korea, 31 J. Evaluation Clin. Prac. e70074 (2025), https://pmc.ncbi.nlm.nih.gov/articles/PMC11959314.

[78] Regulation (EU) 2019/881 of the European Parliament and of the Council of 17 April 2019 on ENISA (the European Union Agency for Cybersecurity) and on information and communications technology cybersecurity certification and repealing Regulation (EU) No 526/2013 (Cybersecurity Act), 2019 O.J. (L 151) 1.

[79] Mikołaj Barczentewicz & Kristian Stout, EU’s Cybersecurity Draft Shifts Toward Hard Protectionism, Truth on the Mkt. (Nov. 14, 2023), https://truthonthemarket.com/2023/11/14/eus-cybersecurity-draft-shifts-toward-hard-protectionism.

[80] Mikołaj Barczentewicz & Kristian Stout, How Not to Use Industrial Policy to Promote Europe’s Digital Sovereignty, Truth on the Mkt. (Oct. 5, 2022), https://truthonthemarket.com/2022/10/05/how-not-to-use-industrial-policy-to-promote-europes-digital-sovereignty.

[81] Id.

[82] See, e.g., John Salmon, Louise Crawford, Lavan Thasarathakumar, Daniel Lee, & Giulia Mariuz, EUCS: Controversial Sovereignty Issues Continue to Drive Debate for Cloud Services, Hogan Lovells (Jun. 12, 2024), https://www.hoganlovells.com/en/publications/eucs-controversial-data-sovereignty-issues-continue-to-drive-debate-around-the-eu-certification-scheme-for-cloud-services.

[83] Nigel Cory, Europe’s Cloud Security Regime Should Focus on Technology, Not Nationality, Info. Tech. & Innovation Found. (Mar. 27, 2023), https://itif.org/publications/2023/03/27/europes-cloud-security-regime-should-focus-on-technology-not-nationality; see also Clarifying Lawful Overseas Use of Data Act, Pub. L. No. 115-141, div. V, 132 Stat. 1213, 1213–25 (2018).

[84] Meredith Broadbent, The European Cybersecurity Certification Scheme for Cloud Services, Ctr. for Strategic & Int’l Stud. (Sep. 1, 2023), https://www.csis.org/analysis/european-cybersecurity-certification-scheme-cloud-services.

[85] Id.

[86] Barczentewicz & Stout, supra note 79.

[87] Barczentewicz & Stout, supra note 80.

[88] Press Release, ENISA Launches a Public Consultation on a New Draft Candidate Cybersecurity Certification Scheme in a Move to Enhance Trust in Cloud Services Across Europe, Eur. Union Agency for Cybersecurity ENISA (Dec. 22, 2020), https://www.enisa.europa.eu/news/enisa-news/cloud-certification-scheme.

[89] Barczentewicz & Stout, supra note 79.

[90] Directive (EU) 2022/2555 of the European Parliament and of the Council of 14 December 2022 on measures for a high common level of cybersecurity across the Union, amending Regulation (EU) No 910/2014 and Directive (EU) 2018/1972, and repealing Directive (EU) 2016/1148 (NIS 2 Directive), 2022 O.J. (L 333) 80.

[91] The EU’s Cloud Service Restrictions, Info. Tech. & Innovation Found. (Aug. 26, 2025), https://itif.org/publications/2025/05/25/eu-cloud-service-restrictions.

[92] Broadbent, supra note 84.

[93] See, e.g., Conan French, Brad Carr, & Clay Lowery, Data Localization: Costs, Tradeoffs, and Impacts Across the Economy, Inst. of Int’l Fin. (Dec. 2020), https://www.iif.com/portals/0/Files/content/Innovation/12_22_2020_data_localization.pdf.

[94] The “Real Life Harms” of Data Localization Policies (Ctr. for Info. Pol’y Leadership Discussion Paper 1, Mar. 2023), at 1, available at https://www.informationpolicycentre.com/uploads/5/7/1/0/57104281/cipl-tls_discussion_paper_paper_i_-_the_real_life_harms_of_data_localization_policies.pdf.

[95] French et al., supra note 93; see also Kruthi Venkatesh, The Data Localization Debate in International Trade Law, Ikigai Law (Jun. 22, 2020), https://www.ikigailaw.com/article/273/the-data-localization-debate-in-international-trade-law (“According to most studies, such forced localization measures create a huge burden on businesses, particularly for small and medium-sized enterprises (SMEs), increasing costs up to 30–60% for acquiring local computing facilities and data storage infrastructure. In fact, as per a study conducted by the European Centre for International Policy Economy, forced data localization norms lead to a negative impact on the GDP and considerable impact on investments.”).

[96] Europe Cloud Computing Market Size & Outlook, 2024-2030, Grand View Res. (retrieved Oct. 28, 2025), https://www.grandviewresearch.com/horizon/outlook/cloud-computing-market/europe.

[97] European Cloud Providers’ Local Market Share Now Holds Steady at 15%, Synergy Res. Grp. (Jul. 24, 2025), https://www.srgresearch.com/articles/european-cloud-providers-local-market-share-now-holds-steady-at-15.

[98] Id.

[99] Id.

[100] Matthias Bauer & Philipp Lamprecht, The Economic Impacts of the Proposed EUCS Exclusionary Requirements: Estimates for EU Member States, Eur. Ctr. for Int’l Pol. Econ. (Oct. 2023), https://ecipe.org/publications/eucs-immunity-requirements-economic-impacts.

[101] See, e.g., Peter Swire, DeBrae Kennedy-Mayo, Drew Bagley, Sven Krasser, Avani Modak, &Christoph Bausewein, Risks to Cybersecurity from Data Localization, Organized by Techniques, Tactics and Procedures, 9 J. Cyber Pol’y 20 (2024).

[102] Zach Meyers, Can the EU Afford to Drive Out American Cloud Services?, Ctr. for Eur. Reform (Mar. 2, 2023), https://www.cer.eu/insights/can-eu-afford-drive-out-american-cloud-services.

[103] 50 U.S.C. §§ 1801–1813 (2020).

[104] United States—Measures Affecting the Cross-Border Supply of Gambling and Betting Services, Appellate Body Report, WT/DS285/AB/R (adopted Apr. 20, 2005), summarized at https://www.wto.org/english/tratop_e/dispu_e/cases_e/1pagesum_e/ds285sum_e.pdf.

[105] ICLE Comments to the Department of Commerce and Department of State’s Consultation on the EU Space Act, Int’l Ctr. Law & Econ. (Aug. 13, 2025), https://laweconcenter.org/wp-content/uploads/2025/08/EU-Space-Act-Comments.pdf.

[106] Proposal for a Regulation of the European Parliament and of the Council on the Safety, Resilience and Sustainability of Space Activities in the Union, 2025/0335 (COD) (Jun. 25, 2025).

Regulatory Comments

ICLE Comments to the EPA on Greenhouse Gas Reporting Program

I. Introduction and Overview The Environmental Protection Agency (EPA) is proposing to amend the Greenhouse Gas Reporting Program (GHGRP) to remove emissions-reporting requirements for most . . .

I. Introduction and Overview

The Environmental Protection Agency (EPA) is proposing to amend the Greenhouse Gas Reporting Program (GHGRP) to remove emissions-reporting requirements for most source categories except for petroleum and natural-gas systems, and to suspend reporting requirements for those categories until 2034.[1] The International Center for Law & Economics (ICLE) is a nonprofit, nonpartisan research organization whose core mission is to promote the application of law & economics methodologies to inform public-policy discussion. Our work focuses on developing intellectually rigorous, data-driven analyses to foster efficient policy solutions that enhance consumer welfare and global economic growth. ICLE scholars have written on the costs of disclosure rules,[2] including how they can violate the U.S. Constitution.[3]

The current GHGRP is a failure on both fronts. The costs of the program are substantial relative to its purported benefits, and it presents serious constitutional questions, including both compelled speech and separation-of-powers issues. The EPA is right to take this important action to amend the program’s obligations to bring it in line with its statutory authority under the Clean Air Act (CAA)[4] and to promote economic efficiency.[5]

The costs of the required disclosures are likely significantly underestimated, while their benefits are simply assumed. The EPA’s current estimates of the costs to regulated businesses are considerably less than the Securities and Exchange Commission’s (SEC) estimate for compliance with a similar emissions-disclosure rule. Moreover, these estimated compliance costs fail to include other dynamic effects of the disclosure regime, including that capital may flow away from the energy sector, to the detriment of innovative U.S. firms that rely on it.

Legally, the EPA’s reliance on Section 114 of the CAA as its statutory authority for the GHGRP is currently on shaky ground. According to the statute, the EPA “may require” certain record keeping, reports, and other requirements for the purpose of “developing or assisting in the development of any implementation plan” under the agency’s authority granted elsewhere in the CAA, to include “determining whether any person is in violation of any such standard or any requirement of such a plan” or “carrying out any provision of this chapter.”[6] The GHGRP has grown significantly to include 47 source categories, for most of which the EPA has never developed any regulations, nor displayed any intent to do so. In other words, these report mandates are not for any authorized statutory purpose but are aimed instead at forcing various industries to publicly account for their contributions to climate change. Based on recent Supreme Court precedents, the current rule invites First Amendment challenges, as well as statutory authority and Major Questions Doctrine challenges.

The EPA’s proposed amendment to the GHGRP would bring the program into alignment with the Constitution and promote more efficient allocation of capital in the vital U.S. energy sector.

II. A Cost-Benefit Analysis of GHGRP Reporting Requirements

A core principle of the law & economics methodology holds that regulation should (1) correct demonstrated market failures; (2) match the regulatory tool to the nature of the market failure; and (3) do so only when the benefits of intervention exceed its costs.[7]

Disclosure rules typically are premised on the argument that regulated entities would not reveal relevant information to the public, resulting in market failures due to asymmetric information. Therefore, it is argued, mandated disclosures allow the public to adjust accordingly. The benefits of mandatory disclosure rules are often assumed to be high, but what is often not sufficiently considered are the costs.

Here, the benefits to the public of being able to ascertain the relative greenhouse-gas emissions of various industry participants have largely been assumed, without analysis. The SEC’s similar disclosure mandate rule was promulgated on grounds that it would assure investors they have a complete picture of the climate-related risks faced by publicly traded companies, which could affect the value of those companies’ securities.[8] For the GHGRP, there is instead a bare assumption that the public benefits in some unspecified way from access to similar information. The EPA notes in its proposal that the primary benefits are derived by government entities that use the information for calculating tax credits or for the terms of certain state programs.[9]

The marginal benefit of this disclosure rule is likely to be small. For instance, there are other federal surveys that could be used to estimate greenhouse-gas emissions. Moreover, the states could collect needed data under their own authorities, while taxing authorities could require other means to qualify for tax credits. There is little additional benefit from the GHGRP’s reporting requirements either to the general public’s understanding of emissions or for the purposes of effectively administering government programs or regulations.

More importantly, the costs of the current rule are likely severely undercounted. First, there are reasons to doubt the estimated compliance costs are accurate. Second, the costs in a more dynamic analysis may be significantly higher than those compliance costs suggest.

The EPA estimates that suspending the reporting requirements will save $303 million annually.[10] Divided among the roughly 8,200 regulated entities, the total comes to $36,951.22 per entity. But the SEC’s proposed rule estimated total compliance costs of $500,000 for the average regulated entity in the first year of compliance and $375,000 in subsequent years, with the compliance costs for emissions disclosures alone to be $151,000 in the first year and $67,000 annually in subsequent years.[11] While the SEC’s regulations applied to different entities than those under GHGRP, and also include additional requirements, it appears likely that industry is directionally correct in arguing the EPA’s estimated costs of compliance are too low.

Moreover, the EPA almost certainly underestimates the total costs of the GHGRP disclosure rule.[12] For instance, continuous threats of litigation against energy companies for alleged harms associated with greenhouse-gas emissions surely count as costs for the regulated entities subject to these reporting requirements. GHGRP data is a goldmine for plaintiffs’ lawyers seeking to bring action against targets that allegedly knew of alleged harms to which they allegedly contributed.

A dynamic analysis of these costs would suggest that capital would flow away from the energy-sector participants subject to the disclosure rule, as it would reduce the likely returns on investment. A safer bet would be in those industries not subject to the disclosure rules and their associated costs. Moreover, reduced investment in the energy sector could lead to harms far outside that sector, as much of the economy is fundamentally reliant on the production and distribution of low-cost energy.[13]

In sum, in conducting cost-benefit analysis of this proposed amendment to the GHGRP rule, the EPA should be sure to evaluate whether the marginal benefits of the current mandated disclosures outweigh their likely vastly underestimated costs. The proposed amendment to free most sources from the GHGRP’s disclosure requirements and to forego reporting requirements for the oil and natural-gas sector until 2034 would appear to make economic sense.

III. Constitutional Issues with the Current Rule

While the economic rationale alone would justify the EPA using its discretion to amend the GHGRP reporting requirements, intervening Supreme Court precedent on compelled speech and the limits on administrative-agency discretion since the original rule was adopted may mean the proposed amendment is legally necessary.

A. First Amendment and Compelled Speech

The current GHGRP rule may violate the First Amendment, in that it compels regulated entities to produce and publish data conveying a message that they are causing environmental harm and contributing to climate change. Supporters of the reporting requirements would argue this is mere regulation of conduct or, at most, compelled commercial speech. But the caselaw since this original rule was adopted suggests that it would likely be subject to heightened First Amendment scrutiny.

In National Institute of Family and Life Advocates v. Becerra,[14] the Supreme Court declined to apply a lower level of scrutiny to the disclosures at issue because it was not “purely factual and uncontroversial information about the terms under which… services will be available.”[15]

Here, the information is not necessarily purely factual and uncontroversial, and the theories that underlie the rule could be the basis of future litigation and regulation targeting the regulated entities.[16] Litigants both public and private have used emissions data like that collected pursuant to the GHGRP in complaints to show that energy companies knew of the harms they allegedly caused. States also use the data as part of their programs.

But just as importantly, the reporting requirements likewise aren’t simply a description of services that will be available. A given firm’s emissions levels are not part of any proposed bargain. As the Court has stated, “precedents define commercial speech as ‘speech that does no more than propose a commercial transaction.’”[17] Similar to the notice required in NIFLA, these reporting requirements are “in no way relate[d]” to the energy-sector products and services that these entities provide.[18]

What this means is that the current reporting requirements, if challenged, may have to face strict scrutiny. Under such scrutiny, the rule would have to be narrowly tailored to a compelling government interest. As noted above, the reporting requirements would fail such a cost-benefit test. The marginal benefits of the reporting requirements are almost certainly low, while the costs—including regulated firms’ potential liability in lawsuits based on the compelled speech—could very well be high.

This is not mere academic quibbling. There are two pending First Amendment lawsuits in federal courts against California’s SB 253 and SB 261 that would require similar greenhouse-gas emissions disclosures. A First Amendment challenge against the SEC climate-risk disclosure rule is also currently held in abeyance by the 8th U.S. Circuit Court of Appeals. The EPA is right to amend the GHGRP rule by limiting the entities subject to its requirements.

B. Separation of Powers

The current GHGRP rule could also violate the Constitution’s separation of powers. In ending its doctrine of Chevron deference[19] and continuing to apply the Major Questions Doctrine,[20] the Supreme Court has made clear that administrative agencies must have clear statutory authority for their rules. The current GHGRP rule appears to far exceed the statutory authority grated the EPA by the CAA. The EPA is right to amend the rule to bring it in line with its statutory authority.

The EPA is no stranger to challenges to its statutory authority. The Supreme Court has made clear in multiple cases involving their rulemakings that “something more than a merely plausible textual basis for agency action is necessary” when claiming “unheralded regulatory power over a significant portion of the economy.”[21] Regulating all the energy-related businesses subject to the GHGRP is a significant portion of the economy.

The textual basis for imposing reporting requirements on most sources currently subject to GHGRP is slim. Authority under Section 114 of the CAA limits the EPA’s ability to collect information to the purposes of developing state implementation plans, setting performance standards, or determining compliance with specific statutory programs.[22] There is no basis under the statute to create perpetual reporting obligations unrelated to those purposes, as the existing GHGRP reporting requirements do.

Moreover, when Congress enacted CAA Section 136, it directed the EPA to impose certain obligations on petroleum and natural-gas producers starting in 2034.[23] Pursuant to those obligations, the EPA is authorized to track emissions and modify the rule here.[24] This suggests that the authority to impose reporting requirements was not already present in Section 114.[25]

Accordingly, the EPA must act according to its statutory authority. Here, that means amending the GHGRP reporting requirements to be consistent with CAA Section 114. Since the EPA has not established any specific emissions regulations, nor does it have any plans to do so until 2034, when it exercises its authority pursuant to CAA Section 134 in relation to petroleum and natural-gas producers, the proposed amendment is necessary to effectuate congressional intent.

Conclusion

The best way forward for the EPA is to adopt the proposed rule in this proceeding. This would be consistent with both the underlying law and economics. The U.S. energy sector is too important to be subject to agency overreach, as exemplified in the current GHGRP rule.

[1] Proposed Rule, Reconsideration of the Greenhouse Gas Reporting Program, 90 Fed. Reg. 44591 (Sep. 16, 2025), available at https://www.govinfo.gov/content/pkg/FR-2025-09-16/pdf/2025-17923.pdf  [hereinafter “Proposed Rule”].

[2] See Geoffrey A. Manne, The Hydraulic Theory of Disclosure Regulation and Other Costs of Disclosure, 58 Ala. L. Rev. 473 (2007).

[3] Amicus Brief of the International Center for Law & Economics in Support of Plaintiff’s Motion for Second Preliminary Injunction, NetChoice, LLC v. Bonta, Case No. 5:22-cv-08861-BLF (Dec. 14, 2022), available at https://laweconcenter.org/wp-content/uploads/2024/11/ICLE-Amicus-NetChoice-v.-Bonta-Northern-District-Court.pdf.

[4] 42 U.S.C. §7414.

[5] See Exec. Order No. 14,192, Unleashing Prosperity Through Deregulation, 90 Fed. Reg. 9065 (Feb. 6, 2025).

[6] 42 U.S.C. §7414.

[7] Stephen Breyer, Regulation and Its Reform (1982) 191 (“Our examination of market defects, classical modes of regulation, and alternative regimes suggest that regulatory failure sometimes means a failure to correctly match the tool to the problem at hand.”), 184 (“It should be painfully apparent that whatever problems one has with an unregulated status quo, the regulatory alternatives will also prove difficult.”)

[8] See U.S. Securities & Exchange Commission, The Enhancement and Standardization of Climate-Related Disclosures for Investors, Release No. 33-11275 at 10-11 (May 28, 2024), https://www.sec.gov/files/rules/final/2024/33-11275.pdf.

[9] Proposed Rule at 44598-99.

[10] Id. at 44596, 44599, 44603.

[11] SEC, supra note 8, at 739-40.

[12] See Manne, supra note 2, at 11-12 (arguing that “while the direct cost” of disclosure regulation is positive, “the indirect costs of regulations may be far more substantial”).

[13] See, e.g., Clark Savage, Germany Blows Up Last Nuclear Plant Towers While Economy Collapses Under Net Zero Energy Policies, Energy News Beat (Oct. 27, 2025), https://energynewsbeat.co/germany-blows-up-last-nuclear-plant-towers-while-economy-collapses-under-net-zero-energy-policies (noting how the German economy is in crisis because of poor energy policies).

[14] 585 U.S. 755 (2018).

[15] Id. at 768 (quoting Zauderer v. Office of Disciplinary Counsel of Supreme Court of Ohio, 471 U.S. 626, 651 (1985)).

[16] Cf. Janus v. Am. Fed. of State, County, & Mun. Employees, Coun. 31, 585 U.S. 878, 913-14 (2018) (identifying climate change as a “controversial” and “sensitive political” subject).

[17] Harris v. Quinn, 573 U.S. 616, 648 (2014) (quoting United States v. United Foods, Inc., 533 U.S. 405, 409 (2001)).

[18] NIFLA, 585 U.S. at 769.

[19] See Loper Bright Enterprises v. Raimondo, 603 U.S. 36 (2024).

[20] See West Virginia v. EPA, 597 U.S. 697 (2022); Utility Air Regulatory Group v. EPA, 573 U.S. 302 (2014).

[21] West Virginia, 597 U.S. at 722, 723 (quoting UARG, 573 U.S. at 324).

[22] See 42 U.S.C. §7414.

[23] See 42 U.S.C. 7436.

[24] 42 U.S.C. 7436(a)(4); (h).

[25] Cf. FDA v. Brown & Williamson Tobacco Corp., 529 U.S. 120, 160 (2000) (“Given this history and the breadth of the authority that the FDA has asserted, we are obliged to defer not to the agency’s expansive construction of the statute, but to Congress’ consistent judgment to deny the FDA this power.”)

Regulatory Comments

ICLE Comments to OSTP on AI Regulatory Reform

Executive Summary These comments from the International Center for Law & Economics analyze the economic effects of artificial-intelligence (AI) governance and recommend a policy of strategic forbearance. Because AI is...

Executive Summary

These comments from the International Center for Law & Economics analyze the economic effects of artificial-intelligence (AI) governance and recommend a policy of strategic forbearance. Because AI is a general-purpose technology with a great degree of uncertainty about its potential future pathways, it would be preferable to apply existing, technology-neutral statutes—such as those governing fraud, discrimination, and product safety—while gathering empirical evidence, rather than to enact premature, prescriptive mandates. This approach preserves the “option value” of waiting for better information before imposing irreversible regulatory costs.

Current barriers to AI deployment stem from two primary sources: federal regulatory mismatch and state-level market fragmentation. Many existing federal regulations are structurally incompatible with AI systems because they embed human-centric assumptions. In transportation, Federal Aviation Administration (FAA) rules for pilot certification and National Highway Traffic Safety Administration (NHTSA) standards for vehicle controls assume a human operator, preventing the approval of autonomous systems. In health care, the Food and Drug Administration’s (FDA) premarket approval process is designed for static physical devices, which conflicts with continuously learning diagnostic algorithms. Similar mismatches exist in financial services under the Equal Credit Opportunity Act and in health-care reimbursement under Medicare’s telehealth rules.

At the state level, a growing patchwork of conflicting AI regulations—such as those enacted in Colorado, California, and New York City—creates substantial economic burdens with high compliance costs. This fragmentation also creates extraterritorial effects, where one state’s restrictive law may become a de facto national standard, burdening interstate commerce.

This paper proposes a two-part framework to address these barriers.

  1. Federal administrative action: Agencies should use existing administrative flexibility—including waivers, pilot programs, and conditional approvals—to permit AI deployment and data gathering. The Commercial Space Launch Amendments Act of 2004 provides a successful precedent for this model. Agencies must also conduct a systematic audit to identify and modernize human-centric regulations, replacing them with performance-based standards.
  2. Targeted congressional preemption: Congress should enact legislation that preempts state and local laws regulating the design, development, training, and validation of AI models. This preemption, modeled on the Airline Deregulation Act, would harmonize the national market. It would simultaneously preserve states’ authority to enforce general, technology-neutral laws (g., consumer-protection statutes) and the authority of federal agencies like the Federal Trade Commission (FTC) and the Equal Employment Opportunity Commission (EEOC) to police demonstrated harms.

I. Introduction and Overview

The Office of Science and Technology Policy (OSTP) is seeking public input to identify federal laws, regulations, and administrative processes that unnecessarily restrict the development and adoption of artificial intelligence (AI) development in the United States.[1] The International Center for Law & Economics (ICLE) is a nonprofit, nonpartisan research organization whose core mission is to promote the application of law & economics methodologies to inform public-policy discussion. Our work focuses on developing intellectually rigorous, data-driven analyses to foster efficient policy solutions that enhance consumer welfare and global economic growth. ICLE previously submitted comments to OSTP regarding national priorities for AI[2] and the development of an AI action plan,[3] and to the National Telecommunications and Information Administration (NTIA) regarding AI accountability policies.[4]

OSTP’s request for information (RFI) asks respondents to identify federal statutes, regulations, and policies that unnecessarily hinder AI development, deployment, and adoption. The request organizes potential barriers into five categories: regulatory mismatch, structural incompatibility, lack of regulatory clarity, direct hindrance, and organizational factors.

Our analysis rests on three economic propositions. First, as was the case with the introduction of wired electric power or the commercial internet, AI is a general-purpose technology whose full economic and social applications remain uncertain.[5] Promulgating technology-specific regulations in such circumstances may foster what economists call targeting errors: rules that are simultaneously too broad (prohibiting beneficial uses) and too narrow (failing to address actual harms).[6]

Second, the compliance costs that arise from fragmented or overly prescriptive regulation function as barriers to entry, particularly for smaller firms that cannot easily absorb the fixed costs of legal review and documentation.

Third, existing legal frameworks already address most AI-related harms through technology-neutral statutes. Indeed, agencies like the Federal Trade Commission (FTC), Equal Employment Opportunity Commission (EEOC), and Food and Drug Administration (FDA) already enforce existing laws against practices such as deception, discrimination, and unsafe products, regardless of whether these issues arise from algorithmic tools or traditional methods.

These principles support several concrete recommendations:

  • The federal government should conduct a systematic audit of regulations that embed human-centric assumptions incompatible with adaptive or autonomous systems, prioritizing modernization in transportation, health care, and financial services.
  • Agencies should expand their use of existing administrative flexibilities—waivers, pilot programs, conditional approvals, and time-limited experimental authorities—to enable lawful AI deployment, while gathering evidence about actual risks and benefits.
  • The Office of Management and Budget (OMB) should coordinate interagency guidance to clarify how existing statutes apply to AI systems, with the aim of preventing duplicative or conflicting interpretations across agencies.
  • Congress should establish targeted preemption of conflicting state laws that regulate the design, development, and training of AI models in order to prevent a compliance patchwork that fragments the national market.
  • Agencies should incorporate formal innovation-impact assessments into cost-benefit analysis for AI-related rulemakings, quantifying effects on market entry, competition, and U.S. technological competitiveness.
  • Future AI regulations should include sunset provisions and mandatory periodic review to ensure rules adapt as the technology evolves.

II. Strategic Forbearance and the Option Value of Information

A core principle of the law & economics methodology holds that regulation should (1) correct demonstrated market failures; (2) match the regulatory tool to the nature of the market failure; and (3) do so only when intervention benefits exceed costs.[7]

Judge Richard Posner, formerly of the 7th U.S. Circuit Court of Appeals, and Cass Sunstein of Harvard Law School have each written extensively on the problem of regulating under uncertainty.[8] When regulators possess limited information about a new technology’s risks and benefits, prescriptive rules often impose costs that exceed their welfare gains.

AI presents an acute example of this uncertainty problem. AI technologies encompass everything from simple pattern recognition in manufacturing quality control to complex language models that generate text and code, as well as advanced multimodal systems capable of producing realistic images, artwork, and dynamically generated video content. Its applications span health-care diagnostics, financial underwriting, transportation logistics, agricultural monitoring, and scientific research. No single regulatory framework can efficiently govern such heterogeneity.

Adam Thierer of the R Street Institute has documented how premature and overly rigid regulation of nascent technologies can create path dependencies that persist long after the original rules become obsolete. His analysis of telecommunications regulation in the 1980s and 1990s illustrates the ways that prescriptive mandates delayed the deployment of digital networks and mobile telephony.[9]

The economic concept of option value helps to explain why regulatory forbearance can enhance consumer welfare. When regulators act prematurely, they foreclose the option to gather more information through market experimentation. By waiting, they preserve the ability to craft more precise rules based on observed outcomes, rather than speculation about hypothetical risks.[10] As ICLE’s Gus Hurwitz and Geoffrey Manne explain:

Regulation as a discovery process, in its simplest formulation, asks regulators to consider that they might be wrong. That they might be asking the wrong questions, collecting the wrong information, analyzing it the wrong way—or even that Congress has given them the wrong authority or misunderstood the problem that Congress has tasked them to address. And, in response to these concerns, regulation as a discovery process asks regulators to build them into the regulatory process itself. This is because regulation does not operate like a competitive market. If Amazon Prime had not been the successful idea that it was, consumers would not have adopted it, other firms would have obtained competitive advantage over Amazon, and the idea would have fallen into the dustbin of history. But when an agency promulgates a rule pursuant to APA processes, that rule takes on the force of law—good or bad, there is no market mechanism by which it will succeed [or] fail.[11]

The Commercial Space Launch Amendments Act of 2004 (CSLAA) provides a successful precedent for the regulation-as-a-discovery-process approach.[12] Congress recognized that applying traditional aerospace regulations, which were designed for government-operated vehicles, would prevent the development of commercial human spaceflight. The CSLAA set safety guidelines for U.S. commercial human spaceflight under the Federal Aviation Administration (FAA), requiring FAA oversight at all launches and landings but prohibiting safety regulations until 2023, unless a serious incident occurred.

Under CLSAA’s rules, space-tourism operators must inform participants of launch and reentry risks in writing, disclose vehicle safety records, and obtain participants’ informed consent. This was not deregulation, as the FAA retained authority to license launches, investigate accidents, and enforce safety standards for the general public. Operators remain liable for damages under common law tort. The CSLAA simply delayed prescriptive regulation of specific design features until there were enough flights to provide an empirical basis for requirements.

Two decades later, this forbearance policy has enabled the growth of a commercial space industry that includes reusable rockets, private space stations, and lunar landers—technologies that did not exist when the CSLAA passed.[13] The FAA now possesses sufficient flight data and operational experience to develop performance-based safety standards grounded in evidence, rather than speculation.

The CSLAA helped to establish a thriving U.S. commercial space industry by granting investors and innovators a stable and predictable regulatory environment. The law’s demonstrated success may now offer lessons for AI governance. Agencies overseeing AI-related markets should similarly monitor real-world deployments: observing how developers test systems, how deployers update models, and what failures occur in practice. Regulators can use these insights to craft targeted rules that address actual problems without limiting beneficial uses.

The CSLAA also demonstrates that the common critique of regulatory forbearance—that it amounts to “doing nothing” in the face of risk—is misplaced. Strategic forbearance is not synonymous with regulatory inaction or abdication. It is an active governance strategy focused on the gathering of information. The CSLAA sequenced the regulation rather than eliminating it. It created a legal framework for learning, data collection, and supervised experimentation. This reframes the policy debate from an either-or proposition of whether to regulate into a framework for developing evidence-based regulation under conditions of high uncertainty.

The cost of premature regulation is not speculative. In 2022, the Information Technology & Innovation Foundation calculated that, over a period of a decade, a patchwork of state privacy laws imposes costs exceeding $1 trillion on firms that operate in multiple states, with small businesses bearing at least $200 billion of this total.[14] The report documented how divergent definitions of “personal information,” “consent,” and “automated decision-making” force companies to maintain separate compliance systems for each jurisdiction.

III. Regulatory Mismatch and Modernization Priorities

The RFI identifies regulatory mismatch as occurring when existing requirements are based on assumptions about human operation that do not align with AI capabilities or operational models.[15] When regulations embed human-centric assumptions, they create not just paperwork burdens but genuine resource costs, as firms are forced to either forgo beneficial technologies or maintain parallel compliance systems.

A. Transportation: Human-Operator Assumptions

The FAA’s pilot-certification regime illustrates an example of the problem of regulatory mismatch. Title 14 of the Code of Federal Regulations, Part 61, establishes requirements for airman certificates. Section 61.3 mandates that no person may act as a required pilot-flight crewmember unless that person holds the appropriate certificate, has it in their physical possession, and presents it for inspection upon request. Section 61.23 further requires an FAA-issued medical certificate. Section 61.39 specifies prerequisites for practical tests, including ground training in topics such as the physiological factors that may affect pilot performance.

While these requirements are perfectly sensible for human pilots, they are absurd for autonomous flight systems. An AI does not have a cardiovascular system and cannot be impaired by alcohol or prescription drugs.

The National Highway Traffic Safety Administration (NHTSA) faces an analogous problem with autonomous vehicles. The existing Federal Motor Vehicle Safety Standards assume human drivers. Standard No. 114, for example, requires theft-protection devices, including a key-locking system and audible warnings.[16] Standard No. 135 requires light-vehicle brake systems to be activated by foot control.[17]

NHTSA has responded to the emergence of autonomous driving systems by allowing manufacturers to file petitions under 49 USC § 30113, which permits limited exemptions for vehicles that provide an equivalent or superior level of safety. But the petition process is resource intensive. For example, General Motors submitted a petition in January 2018 seeking exemptions for a self-driving vehicle design based on its Chevrolet Bolt platform.[18] The agency spent 15 months reviewing the GM petition before seeking public comment. The agency did not issue a final decision before GM withdrew the petition in 2020. Earlier this year, U.S. Transportation Secretary Sean Duffy confirmed that the exemption process has been “bogging developers down in unnecessary red tape that makes it impossible to keep pace with the latest technologies.”[19]

The economic solution is not to eliminate safety requirements but to refocus them on performance outcomes, rather than specific human-centered processes. Instead of requiring that a vehicle have a steering wheel operated by a licensed driver, regulations could require that the vehicle demonstrates the capability to maintain lane position, avoid obstacles, and respond to traffic-control devices.

B. Health Care: Static Device Assumptions and Continuous Learning

The FDA’s regulatory framework for medical devices presents a different form of mismatch. The premarket approval process, codified in 21 CFR Part 814, was designed for physical devices like pacemakers and artificial joints. A manufacturer demonstrates safety and effectiveness through clinical trials of a fixed device design, receives approval, and then produces identical copies. Any significant modification to the approved device requires a new submission for FDA review.

This model creates structural problems for AI-enabled medical software that learns from real-world data. Consider a diagnostic algorithm that analyzes radiology images to detect potential tumors. The system’s accuracy improves as it processes more cases and incorporates feedback from radiologist reviews. Under traditional device regulation, these improvements could constitute modifications that require FDA review, effectively freezing the algorithm at its initial, less-accurate state.

The FDA has attempted to address this problem through its Predetermined Change Control Plan guidance, finalized in December 2024 and updated in August 2025.[20] The guidance allows manufacturers to specify in advance what types of modifications they plan to make post-market, the protocols to implement and validate those changes, and the monitoring plan to ensure continued safety and effectiveness.

A more systematic solution would acknowledge that AI-enabled medical devices are fundamentally different from static physical devices. Rather than requiring upfront approval of a fixed system, the FDA could approve a manufacturer’s testing, monitoring, and validation infrastructure. If the manufacturer demonstrates robust protocols for detecting degraded performance, validating updates against clinical benchmarks, and monitoring real-world outcomes, the FDA could permit continuous improvement within defined boundaries.

C. Financial Services: Model Opacity and Explanation Requirements

The Equal Credit Opportunity Act (ECOA), implemented through Regulation B, requires creditors who deny credit or take other adverse action to provide specific reasons for that action.[21] The Consumer Financial Protection Bureau’s (CFPB) Circular 2022-03 clarifies that this requirement applies to creditors using complex algorithms, rejecting arguments that model opacity could excuse the lack of specific reasons.[22]

This creates a regulatory mismatch when lenders rely on machine-learning models that are not easily interpretable. Deep neural networks and similar algorithms do not produce transparent “reasons” for their decisions—unlike models that yield clear decision trees, regression coefficients, or ranked variable importance.[23] As a result, lenders face costly choices: they can forgo these non-interpretable models even when such models better distinguish creditworthy from uncreditworthy applicants; they could construct post-hoc explanations after decisions are made; or they could invest in developing model-agnostic explanatory tools. Yet none of these strategies directly advance the underlying policy goal: ensuring that credit-approval rates for protected classes do not significantly differ from those for similarly qualified applicants in comparison groups.

IV. State Regulatory Fragmentation and the Economics of Preemption

While federal regulatory mismatch and structural incompatibility create barriers to AI deployment, the proliferation of inconsistent state laws poses a distinct economic threat.[24] A patchwork of state requirements imposes costs that grow multiplicatively with the number of jurisdictions. The National Conference of State Legislatures (NCSL) reports that state lawmakers introduced more than 1,100 AI-related bills nationwide in the 2025 legislative sessions.[25] Dozens of states have enacted legislation or established task forces to study AI regulation. Just four—California, Illinois, New York, and New Jersey—have introduced more than 25% of all state-level AI-related bills.

The definitional inconsistency across these laws is economically significant. Colorado’s SB 24-205, which was amended to take effect June 30, 2026,[26] requires a developer of a high-risk AI system to take reasonable care to protect consumers from any known or reasonably foreseeable risks of “algorithmic discrimination.” The law defines “high-risk artificial intelligence system” as any AI system that makes or is a substantial factor in making a “consequential decision,” which it defined as decisions that have legally material or similarly significant effects on the provision of education, employment, financial services, government, health care, housing, insurance, or legal services.

California began enforcing new rules earlier this year that regulate how employers use AI and automated decisionmaking systems in hiring and employment.[27] These regulations, part of the state’s Fair Employment and Housing Act, aim to prevent discrimination by ensuring that AI tools don’t unfairly disadvantage job applicants or employees based on protected traits like race, gender, or age. Employers must keep records of their AI-related employment data for four years and are responsible for any discriminatory outcomes, even if the tools come from outside vendors.

Similarly, New York City’s Local Law 144 imposes bias-audit requirements specifically for automated employment-decision tools.[28] The law defines such tools as computational processes, derived from machine learning, statistical modeling, data analytics, or AI, that issue simplified outputs that are a substantial factor in employment decisions.

These divergent definitions force developers to maintain separate compliance systems for different jurisdictions. An employment-software provider serving clients in New York City, Colorado, and California must track three different sets of definitions, documentation requirements, audit procedures, and disclosure obligations. As more states continue to explore legislation in this area, this problem of fragmentation will only compound.

A. The Extraterritoriality Problem and Constitutional Economics

State AI regulations do not simply impose local costs on local firms. Because AI models are typically developed for national or global deployment, a restrictive state law effectively sets the standard for all states. In practice, this extraterritorial application violates the principles of federalism and creates economic inefficiency.

For its part, California has taken a piecemeal approach across multiple statutes. AB 2013 requires generative-AI providers to publish documentation about the data used to train their models.[29] SB 942 requires persons creating, coding, or otherwise producing generative-AI systems to provide a publicly accessible detection tool and to make certain disclosures for content produced with the technology.[30] AB 853 requires large online platforms to provide consumers with an easy and conspicuous way to determine if content includes provenance information indicating that it was created or altered by an AI system.[31]

These rules can have significant consequences outside of California. Consider AB 2013, which requires generative AI providers to publish documentation about the data used to train their models. The statute applies to any provider that makes a generative-AI system available to California residents. This requirement is effectively a de facto national standard because it is technically infeasible to train different models for different states.

The dormant Commerce Clause prohibits states from enacting laws that unduly burden interstate commerce, even absent federal legislation.[32] The doctrine rests on an economic rationale: when states impose costs on out-of-state economic activity, they externalize those costs, while capturing local benefits, leading to socially excessive regulation. In Pike v. Bruce Church, Inc., the U.S. Supreme Court held that a state regulation is invalid if “the burden imposed on [interstate] commerce is clearly excessive in relation to the putative local benefits.”[33]

While the Court did recently narrow the scope of the dormant Commerce Clause, the majority in the fractured decision National Pork Producers Council v. Ross decision[34] also upheld the Pike balancing test, which allows challenges to nondiscriminatory state laws where the burdens on interstate commerce outweigh the putative benefits to the state. The majority did not think, however, that changes in market share resulting from some companies choosing to exit the market rather than comply with the law was sufficient to establish a substantial burden on commerce. In other words, so long as out-of-state entities retained the ability to choose whether to serve the particular market, there was no dormant Commerce Clause problem.

In the AI context, this balance weighs heavily against AI-specific state regulations. For developers, avoiding states with burdensome AI laws may not even be possible. For instance, New York’s RAISE Act applies to models that are “deployed” in New York, even if the base model was created elsewhere.[35] Moreover, open-source AI models are often used by downstream users in ways unforeseeable by the original developers; in fact, that is their entire point. There is no way these developers could avoid being subject to state laws on AI if entities within states with such laws use their base model.

Unlike the pork producers in Ross, who could segregate their operations to serve the rest of the country while avoiding California, AI developers will be subject to the most stringent laws regardless of their intent to serve that market. Rather than a choice of whether to serve a particular state, developers would effectively have to choose between complying with the most burdensome state regulations or not releasing their models to the public at all.

By contrast, the local benefits of such rules are likely to be marginal. It would be exceedingly difficult for new AI-specific regulations to generate safety or consumer-protection benefits beyond those already offered by generally applicable, technology-neutral rules. Costly administrative procedures like safety protocols, disclosures, and audits have little correlation to safety.

Nonetheless, as covered in the next section, the limitations of the dormant Commerce Clause should encourage Congress to enact a statute preempting state laws that would effectively destroy a common national market.

B. A Targeted Preemption Framework

Congress should enact targeted preemption of state laws that regulate the design, development, training, and validation of AI models.[36] This preemption should be express—stated clearly in statutory text—and should be limited to avoid unnecessary displacement of state authority.

At a high level, such preemption should cover regulations that target the development of AI, per se, whether explicitly or implicitly. In other words, preemptive federal legislation should prohibit states from imposing requirements on the core processes involved in creating AI and AI-enabled products (as opposed to how users may employ AI technologies). Thus, federal preemption should cover subjects such as the data used to train AI models, the algorithms or techniques used in model development, and the testing and validation procedures applied during development.

States should, however, continue to enforce general laws against fraud, deception, discrimination, and safety violations using their existing authorities under consumer protection, civil rights, and tort law. Moreover, the federal statute should authorize federal agencies with sector-specific expertise to establish performance-based standards for AI systems in their domains.

The Airline Deregulation Act of 1978 provides a successful template. Section 41713(b)(1) of Title 49 prohibits states from enacting or enforcing laws “related to a price, route, or service of an air carrier.”[37] The Supreme Court has interpreted this language broadly to prevent states from using indirect regulation to affect airline operations.

Congress should adopt similarly broad preemption language for AI, prohibiting state laws related to the design, development, training, or validation of AI systems. This would ensure that developers face uniform national standards, rather than fragmented state requirements.

V. Technological Neutrality and the Sufficiency of Existing Law

The RFI asks whether existing policy frameworks are appropriate for AI applications. Most AI-related harms are already addressable through technology-neutral statutes governing fraud, discrimination, unfair commercial practices, and product safety.[38]

A. FTC Authority Over Deceptive and Unfair Practices

Section 5 of the Federal Trade Commission Act prohibits “unfair or deceptive acts or practices in or affecting commerce.”[39] The FTC has made clear that it believes Section 5 authority extends to AI systems. For example, earlier this year, the commission finalized an order against DoNotPay, a company marketing itself as the world’s first “robot lawyer.”[40] The complaint alleged that DoNotPay deceptively claimed its AI could substitute for human lawyers in handling legal matters, when the company had not actually tested its AI’s ability to provide legal assistance and did not employ any attorneys.

In September 2024, the FTC announced Operation AI Comply, a law-enforcement initiative targeting deceptive claims about AI products.[41] The agency issued warning letters to multiple companies and filed complaints against firms that falsely claimed their products used advanced AI technology, or that exaggerated their AI systems’ capabilities.[42]

A technology-neutral framework like Section 5 is economically efficient because it focuses on outcomes (e.g., whether the consumer was deceived or injured) rather than processes (e.g., whether the company used an algorithm).

B. Civil-Rights Law and Algorithmic Discrimination

Civil-rights law provides further examples of the efficacy of technology-neutral regulations. The Civil Rights Act of 1964 (particularly Title VII, governing employment discrimination) and the Fair Housing Act both address discrimination without regard to decisionmaking methods. These statutes prohibit discriminatory outcomes, not discriminatory technologies.

The EEOC issued technical assistance in May 2023 clarifying that Title VII and the Americans with Disabilities Act both extend to employers’ use of algorithmic hiring tools.[43] In September 2023, the EEOC announced a settlement with iTutorGroup for $365,000, resolving allegations that the company programmed its recruiting software to automatically reject applicants over age 55 and certain ages under 55.[44]

The U.S. Justice Department (DOJ) has pursued similar cases under the Fair Housing Act. In 2023, the department filed a statement of interest in Louis et al. v. SafeRent et al., supporting the plaintiffs’ claim that an algorithmic tenant-screening system violated the Fair Housing Act by invoking factors such as credit history and nontenancy related debts, which disproportionately affected Black and Hispanic renters.[45]

These enforcement actions demonstrate that technology-neutral civil-rights laws already reach AI-enabled discrimination. There is no gap in legal authority that would require new AI-specific anti-discrimination statutes. Rather than new laws, what’s needed is clearer guidance on compliance expectations—specifically, what testing and documentation practices will be deemed adequate to demonstrate nondiscriminatory outcomes.

VI. Direct Responses to the RFI’s Specific Questions

A. Question (i): What AI Activities Are Currently Inhibited by Federal Statutes, Regulations, or Policies?

Section III identifies several AI use cases that are currently inhibited by federal statutes, regulations, or policies:

  • The FAA’s pilot-certification regime, which assumes human pilots;
  • The NHTSA’s vehicle-safety standards, which assume human drivers;
  • The FDA’s premarket approval process for physical devices, which delay deployment of continuously learning diagnostic algorithms; and
  • The CFPB’s guidance that Regulation B applies to creditors using complex algorithms.

In addition, there are several other AI applications that are currently inhibited by federal statutes, regulations, or policies.

1. Medicare reimbursement rules regarding telehealth

Medicare reimbursement rules regarding telehealth, particularly 42 CFR § 410.78, are structurally misaligned with the technological capabilities of modern AI in health care. The regulation was designed for an era of episodic, human-to-human telemedicine, creating a framework that substitutes a virtual visit for an in-person one. Its core tenets, such as the requirement for a “two-way, real-time interactive communication” system and geographic restrictions on the patient’s location, are based on a reactive-care model, in which a practitioner responds to a patient’s needs during a scheduled encounter. This approach is incompatible with AI-enabled systems, which operate on a paradigm of continuous, asynchronous data analysis to provide proactive, preventative care.

AI-enabled monitoring shifts the clinical model from reactive to proactive by using algorithms to analyze vast streams of physiological data from wearables and other sensors. This can enable the detection of preclinical signals that precede acute health events. Clinical evidence demonstrates the effectiveness of this approach. AI algorithms have been demonstrated to identify atrial fibrillation with the accuracy of trained cardiologists, enabling earlier intervention to prevent strokes.[46] In critical care, an AI system developed at Johns Hopkins University was found to detect sepsis nearly six hours earlier than traditional methods, reducing patient mortality by 20%.[47] Similarly, AI-powered continuous glucose monitors help prevent acute events like diabetic ketoacidosis in diabetes patients, reducing costly hospital admissions.[48] These technologies provide new capacities for constant vigilance, preventing the need for acute care, rather than simply replacing an office visit.

The specific provisions within the regulation and its associated billing codes create direct barriers to the adoption of these technologies. The regulation’s definition of an “interactive telecommunications system” has a bias toward synchronous, real-time video communication,[49] leaving no clear reimbursement pathway for the value generated by an AI’s asynchronous analysis. Furthermore, reimbursement is tied to the time of specific human practitioners, with no conceptual space to pay for an algorithmic service.

This regulatory misalignment generates significant economic friction, primarily through its interaction with Medicare’s fee-for-service (FFS) payment system. The FFS model rewards the volume of services delivered, creating a financial disincentive for providers to adopt preventative technologies that reduce hospitalizations and procedures. A provider that invests in an AI platform that successfully keeps patients out of the hospital is penalized with lost revenue from those avoided admissions. This arrangement makes the adoption of clinically superior technology economically irrational for the provider, even as it saves the payer money and improves patient outcomes. The current rules fail to provide a sufficient counterincentive to overcome this fundamental conflict.

A durable solution would require a multi-pronged policy approach. First, 42 CFR § 410.78 must be modernized to create a distinct benefit category for asynchronous, algorithm-based monitoring services, decoupling them from the outdated synchronous-communication requirements. Second, the Centers for Medicare & Medicaid Services (CMS) should develop a new reimbursement pathway, with billing codes that compensate for the clinical value of AI-generated insights, such as early risk detection, rather than for process metrics like minutes spent on a call.

2. Federal employee productivity tools

There is a disconnect between the U.S. government’s official pro-innovation stance on AI and the implementation of this policy posture at the agency level.[50] While the White House seeks to remove bureaucratic restrictions, agencies—including the Veterans Affairs Department and Energy Department—have instituted blanket prohibitions on generative-AI productivity tools, citing security concerns.[51] This contradiction stems from gaps in the guidance provided by OMB Memorandum M-24-10, issued in 2024. While the memorandum provided a detailed governance framework for “safety-impacting” and “rights-impacting” AI, it offered no clear pathway to approve low-risk productivity software. In the absence of specific guidance, some agency officials have defaulted to the most conservative position of prohibition.

The opportunity cost of this inaction is substantial. Economic research from the Federal Reserve Bank of St. Louis suggests that adoption of generative-AI tools could increase aggregate productivity by 1.1%, with the average user saving 2.2 hours per week.[52] Studies on specific tasks common in government work show that AI tools accelerate writing by 40% while improving quality by 18%, and programmers using AI assistants complete tasks 55.8% faster.[53] By forgoing these tools, federal agencies are sacrificing potential gains in government efficiency and operational effectiveness.

The current patchwork of agency-level prohibitions is a strategically incoherent application of federal policy. These bans collapse the tiered, risk-based structure intended by OMB M-24-10, whose text implies that not all AI systems warrant the same intensive governance. They also run afoul of what the Brooking Institution has observed is a bipartisan consensus that regulatory efforts should focus on high-impact systems.[54] Furthermore, these prohibitions create a “shadow AI” problem, in which motivated employees will turn to personal devices and commercial accounts to use these tools, moving the activity outside the government’s security perimeter and creating the unmonitored data-handling risks the policies were designed to prevent.

A more effective approach requires the OMB to issue supplemental guidance that formally defines and creates a separate governance track for low-risk AI-productivity tools. Clarifying that simple productivity tools are not subject to the most stringent requirements of M-24-10 would enable agencies to allocate their finite governance resources to those use cases already identified as potentially implicating safety concerns or protected rights.

The practical implementation of this policy would involve transitioning from prohibition to a system of secure application “allowlisting.” This cybersecurity best practice, endorsed by the Cybersecurity and Infrastructure Security Agency, operates on a “default deny” principle, where only explicitly vetted and approved software is permitted to run.[55] The technical feasibility of this model has already been demonstrated by successful pilot projects in secure federal environments, including the Department of Homeland Security’s (DHS) “DHSChat” tool,[56] the FDA’s “Elsa” platform,[57] and the U.S. Army’s “#CalibrateAI” program.[58] These examples illustrate that the primary barrier to adoption is a lack of policy clarity, not a lack of secure technical solutions.

By combining a default-deny architecture with a structured allowlist of pre-approved tools, agencies could safely expand access to low-risk AI applications—such as summarization, document drafting, or data-sorting assistants—without triggering the compliance overhead intended for high-impact systems. This would unlock measurable efficiency gains while maintaining a strong security posture, aligning governance with practical risk management, rather than categorical prohibition.

B. Question (ii): What Specific Federal Statutes, Regulations, or Policies Present Barriers?

Sections III and VI.A identify several specific federal statutes, regulations, or policies that present barriers:

  • 49 U.S.C. § 44703 requires individuals to hold airman certificates meeting specified knowledge, physical fitness, and character standards. The statute’s definition of “airman” as an individual prevents certification of autonomous aircraft systems.
  • 49 CFR § 571.114 requires theft-protection systems, including key-locking steering columns. The standard assumes a human-operated vehicle and is structurally incompatible with autonomous vehicles without steering wheels.
  • 21 CFR § 814 establishes premarket-approval requirements for Class III medical devices based on a model of fixed device designs. The regulation does not accommodate continuously learning algorithms without extensive change-control submissions.
  • 12 CFR § 1002.9 (Regulation B implementing ECOA) requires creditors to provide specific reasons for adverse credit actions. The CFPB has interpreted this to require more detailed explanations than some noninterpretable models can easily generate.
  • Medicare reimbursement rules regarding telehealth, particularly 42 CFR § 410.78, are structurally misaligned with the technological capabilities of modern AI in health care.

C. Question (iii): Where Are Administrative Tools Available but Underutilized?

Section III identifies several administrative tools that are available but underutilized:

  • FAA waivers under 14 CFR § 107.200: The regulation permits waivers of Part 107 requirements for unmanned aircraft operations if the applicant demonstrates safety, but the processing times to obtain these waivers average 90 days. Greater use of categorical waivers for low-risk operations could accelerate beneficial deployments.
  • FDA expedited review pathways under 21 U.S.C. § 360e-3: The Food, Drug, and Cosmetic Act authorizes the FDA to use expedited procedures for breakthrough devices. The agency could apply these pathways more systematically to AI-enabled diagnostic and monitoring systems.
  • NHTSA temporary exemptions under 49 U.S.C. § 30113: The statute permits exemptions from Federal Motor Vehicle Safety Standards for up to two years (extendable to three) for vehicles with safety levels at least equal to the standard’s level. NHTSA could use this authority more proactively for autonomous-vehicle testing.

In addition, the CFPB, Federal Deposit Insurance Corporation (FDIC), and Office of the Comptroller of the Currency (OCC) have authority to approve pilot programs—sometimes referred to as “regulatory sandboxes”—for innovative financial products. Creating more formalized sandbox programs with published entry criteria would reduce uncertainty.

D. Question (iv): What Modifications Would Enable Lawful Deployment While Preserving Regulatory Objectives?

Sections III and VI.A identify several modifications that would enable lawful deployment while preserving regulatory objectives:

  • Transportation:
    • Amend 49 U.S.C. § 40102 to define “operator in command” to include both human pilots and autonomous systems and direct the FAA to establish performance-based airworthiness standards for autonomous aircraft that focus on perception, decisionmaking, communication, and fault tolerance.
    • Amend 49 U.S.C. § 30102 to define “driver” to include automated driving systems capable of performing the entire dynamic-driving task, and direct NHTSA to establish safety-performance standards for such systems that address operational design domains, object and event detection and response, fallback mechanisms, and crashworthiness.
  • Health Care:
    • Amend 21 U.S.C. § 360c to authorize the FDA to create a provisional-approval pathway for AI-enabled medical devices, permitting initial market entry based on promising (but limited) clinical data, coupled with mandatory post-market monitoring, outcome tracking, and confirmatory studies.
    • Amend 42 CFR § 410.78 to authorize Medicare reimbursement for remote patient monitoring using AI-enabled continuous-monitoring systems when clinical evidence demonstrates equal or superior outcomes relative to traditional scheduled consultations, with payment rates reflecting the monitoring’s clinical value.
  • Financial services: Amend 15 U.S.C. § 1691(a) to specify that, when creditors use algorithmic models, the model as a whole constitutes a “policy or practice” for disparate-impact analysis, and establish that creditors satisfy adverse-action notice requirements by providing explanations that meet specified documentation and testing standards, even if the model is not fully interpretable.
  • Federal AI use: OMB should issue clarifying guidance distinguishing between AI systems that require special governance (those making consequential decisions about individuals or affecting safety) and productivity tools that can be used with standard information-security controls. Agencies should maintain allowlists of vetted productivity tools and usage protocols, rather than categorical prohibitions.

E. Question (v): What Forms of Clarification Would Be Most Effective?

Effective forms of clarification include interagency guidance, sector-specific standards, enforcement priority statements, and conditional safe harbors. Together, these measures would give firms clearer expectations, while allowing regulators to adapt as AI evolves.

  • Interagency guidance on technology-neutral enforcement: OSTP should coordinate an interagency working group that includes the FTC, DOJ, EEOC, and sector-specific regulators to develop unified guidance on how existing statutes apply to AI systems. The guidance should emphasize outcomes over process and provide safe harbors for specified testing and monitoring practices.
  • Sector-specific standards for adequate documentation: Agencies should publish model documentation templates aligned with the National Institute of Standards and Technology (NIST) AI Risk Management Framework.[59] For example, the CFPB could specify what testing and monitoring for algorithmic bias would be deemed adequate to satisfy fair-lending obligations. EEOC could identify acceptable statistical tests for adverse-impact analysis.
  • Enforcement priority statements: When statutory language plausibly covers AI but the application of that language remains uncertain, agencies should issue enforcement-priority statements clarifying what conduct they will and will not pursue. For example, the FTC could specify what types of AI-generated-content disclosures it considers adequate to avoid deception claims.
  • Conditional safe harbors: Agencies could establish safe harbors stating that firms following specified practices will not face enforcement action for specified violations. For instance, FDA could create a safe harbor for AI-related medical-device updates that follow predetermined change-control plans, stating that such updates will not be deemed to require new premarket approval.
  • Published evaluation criteria for pilots and waivers: Agencies should publish detailed criteria explaining what evidence applicants must provide to obtain pilot-program approvals or waivers. Criteria should specify acceptable forms of safety demonstration, monitoring protocols, and risk-mitigation measures.

F. Question (vi): How Might Federal Action Address Organizational Barriers?

To strengthen federal capacity for consistent and credible AI oversight, agencies need shared technical resources and evaluation practices, which would include the following actions:

  • Create an OSTP-led AI-evaluation support center: OSTP should establish a center that provides agencies with technical assistance to evaluate AI pilot proposals and waiver requests. The center would maintain evaluation templates aligned with NIST frameworks and host a repository of successful pilot-project case studies.
  • Establish communities of practice: OSTP should convene regular meetings of agency AI coordinators to share lessons learned, discuss evaluation challenges, and develop common approaches to recurring problems.
  • Develop model pilot-program terms: OSTP should work with agencies to develop model legal terms for AI pilot programs, including entry criteria, participant obligations, data-sharing requirements, monitoring protocols, and evaluation metrics.

VII. Recommendations

Based on the foregoing analysis, ICLE respectfully recommends the following actions:

A. Immediate Administrative Actions

To ensure federal oversight keeps pace with rapid advances in AI, agencies need systematic updates to outdated rules and coordinated guidance on enforcement and evaluation. This section outlines a set of institutional reforms—ranging from a federal AI-rule audit to an OSTP-led evaluation support center and innovation-impact assessments—to modernize regulatory frameworks, while preserving accountability and promoting innovation.

  • Conduct a federal AI-rule audit: OSTP should direct agencies to inventory regulations that embed assumptions about human operation, static design, or other characteristics incompatible with AI systems. The audit should prioritize high-impact sectors and identify specific regulatory provisions for modernization.
  • Issue interagency guidance on technology-neutral enforcement: OSTP should convene FTC, DOJ, EEOC, CFPB, and sector regulators to develop unified guidance on how existing statutes apply to AI. The guidance should emphasize that laws prohibiting fraud, discrimination, and unfair practices apply to automated systems.
  • Publish agency playbooks for pilots and waivers: OSTP should work with agencies to develop and publish detailed guidance on obtaining approval for AI pilot programs and waivers. Playbooks should include entry criteria, model application templates, required evidence and testing protocols, and monitoring requirements.
  • Establish an AI-evaluation support center: OSTP should create an interagency center that provides technical assistance for evaluating AI systems, maintains repositories of successful pilots and model terms, develops training materials for agency staff, and coordinates evaluation methodologies across agencies.
  • Adopt innovation impact assessment: OMB should revise Circular A-4 to require agencies conducting cost-benefit analysis for AI-related rules to systematically assess and document innovation impacts, including effects on market entry, dynamic competition, and international competitiveness.

B. Congressional Actions

Federal legislation will be essential to provide consistent, adaptive governance for AI across sectors. This section outlines key congressional actions—targeted preemption, performance-based approval pathways, and regulatory sunset provisions—to harmonize oversight, enable innovation, and ensure accountability as AI technologies evolve.

  • Enact targeted AI preemption legislation: Congress should pass legislation prohibiting states from regulating the design, development, training, or validation of AI models, while preserving state authority to enforce general laws against fraud, discrimination, and safety violations.
  • Authorize performance-based approval pathways: Congress should amend relevant statutes to permit agencies to approve adaptive systems through performance-based standards, as discussed in Sections III and B.
  • Require regulatory sunset and review: Congress should enact legislation requiring that any new AI-specific regulation include either a sunset provision or mandatory periodic review to assess whether the regulation’s benefits continue to exceed its costs as the technologies evolve.

VIII. Conclusion

AI is a general-purpose technology whose applications and potential risks remain incompletely understood. In this circumstance of high uncertainty, regulatory forbearance—defined as maintaining technology-neutral enforcement of existing law while gathering empirical evidence—is likely to produce better welfare outcomes than premature, prescriptive mandates. Existing statutes governing fraud, product safety, discrimination, and unfair commercial practices already reach conduct enabled by AI. The primary challenge is not a legal authority gap but regulatory mismatch and market fragmentation.

Many existing federal regulations embed assumptions about human operation or static product design, creating barriers to beneficial AI deployment. In most cases, these barriers can be addressed through administrative flexibility—such as waivers, pilot programs, conditional approvals, and updated guidance—rather than requiring new statutes.

A distinct threat arises from the proliferation of conflicting state laws. A compliance patchwork imposes costs that grow multiplicatively with jurisdictional divergence; creates barriers to entry that favor incumbents; and allows restrictive states to set de facto national policy through extraterritorial effects. Federal preemption of state laws that regulate the design and development of AI models, paired with technology-neutral federal enforcement, would restore constitutional and economic coherence to the national market.

Rather than creating duplicative AI-specific mandates, agencies should clarify how these technology-neutral laws apply to novel systems. Agencies should also establish safe harbors for firms that follow specified testing and monitoring practices and build internal evaluation capacity. This regulatory approach permits responsible innovation while addressing demonstrated harms and preserves U.S. leadership in a technology central to future economic and strategic competition.

[1] Request for Information: Regulatory Reform on Artificial Intelligence, Off. of Sci. & Tech. Policy (OSTP-TECH-2025-0067, 90 FR 46422, Sep. 26, 2025), [hereafter “RFI”].

[2] Response of the International Center for Law & Economics, Request for Information, National Priorities for Artificial Intelligence, Int’l. Ctr. Law & Econ. (OSTP-TECH-2023-0007, Jul. 7, 2023) available at https://laweconcenter.org/wp-content/uploads/2023/07/OSTP-AI-Comments.pdf [hereafter “Priorities Comments”].

[3] Comments of the International Center for Law & Economics: Request for Information on the Development of an Artificial Intelligence (AI) Action Plan, Int’l. Ctr. Law & Econ. (Mar. 14, 2025) available at https://laweconcenter.org/wp-content/uploads/2025/03/OSTP-AI-2025-comments-v-1.pdf [hereafter “Action Plan Comments”].

[4] Response of the International Center for Law & Economics to the AI Accountability Policy Request for Comment: National Telecommunications and Information Administration, Int’l. Ctr. Law & Econ. (Docket No. 230407-0093, Jun. 12, 2023) available at https://laweconcenter.org/wp-content/uploads/2023/06/NTIA-AI-Comments-final.pdf [hereafter “Accountability Comments”].

[5] Accountability Comments 17.

[6] Priorities Comments 5.

[7] Stephen Breyer, Regulation and Its Reform (1982) 191 (“Our examination of market defects, classical modes of regulation, and alternative regimes suggest that regulatory failure sometimes means a failure to correctly match the tool to the problem at hand.”), 184 (“It should be painfully apparent that whatever problems one has with an unregulated status quo, the regulatory alternatives will also prove difficult.”)

[8] Richard A. Posner, Antitrust in the New Economy, 68 Antitrust L. J. 925 (2001), (“The real problem lies on the institutional side: the enforcement agencies and the courts do not have adequate technical resources, and do not move fast enough, to cope effectively with a very complex business sector that changes very rapidly.”); Isaac Ehrlich & Richard A. Posner, An Economic Analysis of Legal Rulemaking, 3 J. Legal Stud. 257, 277 (1974), (“An important cost of legal regulation by means of rules is thus the cost of altering rules to keep pace with economic and technological change.”); Cass R. Sunstein, Maximin, 37 Yale J. Reg. 940 (Jul. 29, 2020), (“Observers (including regulators) are in circumstances of Knightian uncertainty, where they cannot assign probabilities to imaginable outcomes.”).

[9] See, e.g., Adam Thierer, The Future of Innovation: Is This the End of Permissionless Innovation?, Discourse (Jan. 6, 2021), https://www.discoursemagazine.com/p/the-future-of-innovation-is-this-the-end-of-permissionless-innovation.

[10] See, e.g., Kenneth J. Arrow & Anthony C. Fisher, Environmental Preservation, Uncertainty, and Irreversibility, 88 Q. J. Econ. 312 (1974), (explaining that, when a decision is irreversible and future benefits and costs are uncertain, immediate action eliminates the opportunity to learn more before committing resources; by waiting, society retains an “option value,” i.e., the value of preserving flexibility to act later when uncertainty has been reduced; delaying regulation (forbearance) can be welfare enhancing if immediate action would lock in a costly or suboptimal rule and prevent learning from future information or market responses).

[11] Justin (Gus) Hurwitz & Geoffrey A. Manne, Regulation as a Discovery Process (Oct. 16, 2024), https://ssrn.com/abstract=4721112.

[12] Pub. L. No. 108-492, 118 Stat. 3974 (2004).

[13] See, e.g., The Space Report 2025 Q2 Highlights Record $613 Billion Global Space Economy for 2024, Driven by Strong Commercial Sector Growth, Space Found. (Jul. 22, 2025), https://www.spacefoundation.org/2025/07/22/the-space-report-2025-q2 (the global space economy reached $613 billion in 2024, and the commercial sector made up roughly 78% of that total).

[14] Daniel Castro, Luke Dascoli, & Gillian Diebold, The Looming Cost of a Patchwork of State Privacy Laws, Info. Tech. & Innovation Found. (Jan. 2022), available at https://www2.itif.org/2022-state-privacy-laws.pdf.

[15] RFI 46423 (“Most existing Federal regulatory regimes and policy mechanisms were developed before the rise of modern AI technologies. As a result, they often rest on assumptions about human-operated systems that are not appropriate for AI-enabled or AI-augmented systems.”)

[16] 49 CFR § 571.114.

[17] 49 CFR § 571.135.

[18] Cruise, GM to Seek U.S. Okay for Self-Driving Vehicle Without Pedal, Steering Wheel, Reuters (Oct. 21, 2020), https://www.reuters.com/business/autos-transportation/cruise-gm-seek-us-okay-self-driving-vehicle-without-pedal-steering-wheel-2020-10-21.

[19] David Shepardson, NHTSA Streamlining Self-Driving Car Exemption Reviews, Ins. J. (June 16, 2025), https://www.insurancejournal.com/news/national/2025/06/16/827924.htm.

[20] Marketing Submission Recommendations for a Predetermined Change Control Plan for Artificial Intelligence-Enabled Device Software Functions: Guidance for Industry and Food and Drug Administration Staff, Food & Drug Admin. (Aug. 18, 2025), https://www.fda.gov/media/166704/download.

[21] 12 CFR Part 1002.

[22] Adverse Action Notification Requirements in Connection with Credit Decisions Based on Complex Algorithms, Consumer Financial Protection Circular 2022-03, Consumer Fin. Prot. Bureau (May 26, 2022), (“ECOA and Regulation B do not permit creditors to use complex algorithms when doing so means they cannot provide the specific and accurate reasons for adverse actions”)

[23] See, e.g., Rabia Saleem, Bo Yuan, Fatih Kurugollu, Ashiq Anjum, & Lu Liu, Explaining Deep Neural Networks: A Survey on the Global Interpretation Methods, 513 Neurocomputing 165 (2022).

[24] Action Plan Comments 3 (“This definitional challenge is further complicated by the emerging patchwork of state and local AI regulations that has emerged in the absence of federal guidance. Developers and deployers of AI systems who operate across jurisdictional boundaries face substantial compliance challenges as a result of this regulatory fragmentation. The proliferation of potentially conflicting state regulations also creates significant legal uncertainty that disproportionately burdens smaller innovators and startups, as these entities often lack the resources to navigate complex regulatory environments. This has the potential to further entrench the market positions of larger incumbents.”)

[25] Artificial Intelligence 2025 Legislation, Nat’l Conf. State Legs. (Jul. 10, 2025), https://www.ncsl.org/technology-and-communication/artificial-intelligence-2025-legislation.

[26] Michael J. Laszlo, Colorado’s AI Law Delayed Until June 2026: What the Latest Setback Means for Businesses, Clark Hill (Aug. 28, 2025), https://www.clarkhill.com/news-events/news/colorados-ai-law-delayed-until-june-2026-what-the-latest-setback-means-for-businesses.

[27] Danielle Ochs, 10 FAQs About California’s New Algorithmic Discrimination Rules, Ogletree Deakins (Sep. 16, 2025), https://ogletree.com/insights-resources/blog-posts/10-faqs-about-californias-new-algorithmic-discrimination-rules.

[28] New York City, Local Law No. 144 of 2021, N.Y.C. Admin. Code § 20-870 et seq. (2021), https://www.nyc.gov/site/dca/about/automated-employment-decision-tools.page

[29] Cal. Assemb. Bill 2013 (Irwin) (2024) (to be codified at Cal. Civ. Code §§ 1798), available at https://sjud.senate.ca.gov/system/files/2024-06/ab-2013-irwin-sjud-analysis.pdf.

[30] Cal. S.B. 942, 2023-24 Sess. (Cal. 2024), https://legiscan.com/CA/text/SB942/id/3021807.

[31] Cal. Assemb. Bill 853 (Wicks) (2025) (Ch. 674, Statutes of 2025) (to be codified at Cal. Bus. & Prof. Code §§ 22757.3.1 et seq.), https://legiscan.com/CA/text/AB853/id/3245321.

[32] See Barry Friedman & Daniel T. Deacon, A Course Unbroken: The Constitutional Legitimacy of the Dormant Commerce Clause, 97 Va. L. Rev. 1877 (2011).

[33] 397 U.S. 137 (1970).

[34] 598 U.S. 356 (2023).

[35] New York 6453—A (Mar. 5, 2025).

[36] Action Plan Comments 4 (“[T]he AI Action Plan should establish clear federal guidelines that preempt contradictory state and local regulations, while setting minimum transparency standards appropriate to each category of AI application. The goal of such standards should be to protect consumers without imposing excessive compliance burdens that might stifle innovation. The aim should be to foster functional markets where customers can access the services they demand, not to initiate a new cottage industry for AI compliance lawyers.”)

[37] 49 USC § 41713.

[38] Accountability Comments 15.

[39] 15 U.S.C. § 45.

[40] Press Release, FTC Finalizes Order with DoNotPay That Prohibits Deceptive “AI Lawyer” Claims, Imposes Monetary Relief, and Requires Notice to Past Subscribers, Fed. Trade Comm’n (Feb. 11, 2025), https://www.ftc.gov/news-events/news/press-releases/2025/02/ftc-finalizes-order-donotpay-prohibits-deceptive-ai-lawyer-claims-imposes-monetary-relief-requires.

[41] Michael D. Meuti & Andrew J. Jarzyna, One Year In, FTC’s “Operation AI Comply” Continues Under New Administration, Signaling Enduring Enforcement Focus, Benesch (Oct. 21, 2025), https://www.beneschlaw.com/resources/one-year-in-ftcs-operation-ai-comply-continues-under-new-administration-signaling-enduring-enforcement-focus.html.

[42] Press Release, FTC Announces Crackdown on Deceptive AI Claims and Schemes, Fed. Trade Comm’n (Sep. 25, 2024), https://www.ftc.gov/news-events/news/press-releases/2024/09/ftc-announces-crackdown-deceptive-ai-claims-schemes.

[43] Select Issues: Assessing Adverse Impact in Software, Algorithms, and Artificial Intelligence Used in Employment Selection Procedures Under Title VII of the Civil Rights Act of 1964, Equal Emp’t. Opp. Comm’n (May 18, 2023), https://www.eeoc.gov/select-issues-assessing-adverse-impact-software-algorithms-and-artificial-intelligence-used, available at https://web.archive.org/web/20230519192227/https://www.eeoc.gov/select-issues-assessing-adverse-impact-software-algorithms-and-artificial-intelligence-used#expand.

[44] Press Release, iTutorGroup to Pay $365,000 to Settle EEOC Discriminatory Hiring Suit, Equal Emp’t. Opp. Comm’n (Sep. 11, 2023), https://www.eeoc.gov/newsroom/itutorgroup-pay-365000-settle-eeoc-discriminatory-hiring-suit.

[45] Press Release, U.S. Attorney’s Office Files Statement of Interest in Fair Housing Act Case Alleging Unlawful Algorithm-Based Tenant Screening Practices, Dep’t Just. (Jan. 9, 2023), https://www.justice.gov/usao-ma/pr/us-attorneys-office-files-statement-interest-fair-housing-act-case-alleging-unlawful.

[46] See, e.g., Delivering Advanced AI to Cardiac Monitoring, iRhythm (retrieved Oct. 22, 2025), https://www.irhythmtech.com/us/en/solutions-services/fda-cleared-ai.

[47] Laura Cech, Sepsis-Detection AI Has the Potential to Prevent Thousands of Deaths, Johns Hopkins U. (Jul. 21, 2022), https://hub.jhu.edu/2022/07/21/artificial-intelligence-sepsis-detection.

[48] See, e.g., Chenyang Ji, Tong Jiang, Luolin Liu, Jiale Zhang, & Liangzhen You, Continuous Glucose Monitoring Combined with Artificial Intelligence: Redefining the Pathway for Prediabetes Management, 16 Front. Endocrinol. 1571362 (May 26, 2025).

[49] 42 CFR § 410.78(a)(3) (“Interactive telecommunications system means… multimedia communications equipment that includes, at a minimum, audio and video equipment permitting two-way, real-time interactive communication between the patient and distant site physician or practitioner.”)

[50] Frances M. Green, New Federal Agency Policies and Protocols for Artificial Intelligence Utilization and Procurement Can Provide Useful Guidance for Private Entities, Workforce Bulletin (Apr. 25, 2025), https://www.workforcebulletin.com/new-federal-agency-policies-and-protocols-for-artificial-intelligence-utilization-and-procurement-can-provide-useful-guidance-for-private-entities.

[51] Rebecca Heilweil, More Federal Agencies Join in Temporarily Blocking or Banning ChatGPT, FedScoop (Jan. 9, 2024), https://fedscoop.com/more-federal-agencies-join-in-temporarily-blocking-or-banning-chatgpt.

[52] Alexander Bick, Adam Blandin, & David Deming, The Impact of Generative AI on Work Productivity, Fed. R. Bank St. Louis (Feb. 27, 2025), https://www.stlouisfed.org/on-the-economy/2025/feb/impact-generative-ai-work-productivity.

[53] Shakked Noy & Whitney Zhang, Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence, 381 Science 187 (Jul. 13, 2023).

[54] Sorelle Friedler & Andrew D. Selbst, 5 Points of Bipartisan Agreement on How to Regulate AI, Brookings Inst. (Aug. 15, 2025), https://www.brookings.edu/articles/five-points-of-bipartisan-agreement-on-how-to-regulate-ai.

[55] What the Heck Is Application Allowlisting in CMMC?, Totem.Tech (Apr. 25, 2025), https://www.totem.tech/application-allowlisting-cmmc.

[56] Michael Boyce, DHS’s Responsible Use of Generative AI Tools, Dep’t Homeland Sec. (Dec. 17, 2024), https://www.dhs.gov/archive/news/2024/12/17/dhss-responsible-use-generative-ai-tools.

[57] Press Release, FDA Launches Agency-Wide AI Tool to Optimize Performance for the American People, Food & Drug Admin. (Jun. 2, 2025), https://www.fda.gov/news-events/press-announcements/fda-launches-agency-wide-ai-tool-optimize-performance-american-people.

[58] Jennifer Swanson, #CalibrateAI/Project Athena Update, U.S. Army (Nov. 19, 2024), https://www.army.mil/article/281451/calibrateaiproject_athena_update.

[59] Artificial Intelligence Risk Management Framework (AI RMF 1.0), Nat’l Inst. Stds. & Tech. (Jan. 2023), available at https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.100-1.pdf.

Regulatory Comments

ICLE Comments on EU TTBER and Technology Transfer Guidelines

I. Introduction The International Center for Law & Economics (ICLE) thanks the European Commission for the opportunity to comment to this public consultation on the draft revised Technology Transfer Block...

I. Introduction

The International Center for Law & Economics (ICLE) thanks the European Commission for the opportunity to comment to this public consultation on the draft revised Technology Transfer Block Exemption Regulation (TTBER) and accompanying Technology Transfer Guidelines. ICLE is a nonprofit, nonpartisan research centre devoted to the study of law and economics, and our scholars have written extensively on intellectual property and competition policy. We appreciate the Commission’s efforts to refine the TTBER framework, and we offer our perspective on two key aspects of the Draft Guidelines that raise serious concerns.

A. Safe Harbour for Licensing-Negotiation Groups (LNGs)

The proposal in Section 4.5 of the Draft Guidelines to introduce a safe harbour for licensing-negotiation groups would likely do more harm than good. While intended to address perceived “patent holdup” in standard-essential-patent (SEP) licensing, this policy is based on a flawed premise and risks serious unintended consequences.

There is little empirical evidence of systemic holdup problems in SEP licensing. Studies have indeed found no indication that SEP holders are extracting supra-competitive royalties or undermining technology adoption under the status quo.[1] By contrast, the problem of “patent holdout” (implementers collectively delaying or denying fair payment for SEPs) is well-documented and poses a significant threat to innovation.[2] Indeed, creating an antitrust safe harbour for groups of implementers to jointly negotiate licenses could facilitate collective holdout.

LNGs effectively act as buyers’ cartels, empowering implementers to coordinate against patent holders’ interests. Even with the draft’s proposed safeguards (e.g., open access, transparency, and a cap on jointly negotiated fees), an LNG safe harbour would tilt the negotiating balance disproportionately toward implementers. In turn, this would undermine SEP holders’ incentives to contribute technology to standards and could invite further collusive behaviour among implementers. Notably, a senior U.S. Justice Department (DOJ) official recently criticized the Commission’s support for an automotive LNG as “unfortunate” and difficult to reconcile with sound competition-law principles, warning that such arrangements would likely be treated as a per se unlawful buyers’ cartel in the United States.[3] Endorsing LNGs in the Technology Transfer Guidelines—via the Guidelines’ safe harbour—would therefore create more problems than it solves.

B. Essentiality Checks in Patent Pools

The essentiality checks mandated by the Guidelines in the context of patent pools also raise significant issues. Properly structured patent pools can generate important pro-competitive benefits by reducing transaction costs and bundling complementary patents for one-stop licensing. The existing Technology Transfer Guidelines already provide a safe harbour for pools that include only essential and complementary technologies and abide by fair, reasonable, and non-discriminatory (FRAND) licensing terms.[4] The draft revision, however, goes further by encouraging greater transparency about essentiality verification—specifically, requiring disclosure of any methodology used to assess essentiality and the results of such assessments.[5]

While transparency is generally welcome, imposing additional essentiality-check expectations would burden innovators and pool administrators with costly and redundant procedures. Many patent pools already employ independent experts to evaluate whether submitted patents are truly essential to the relevant standard. Requiring pools to formalize and disclose these checks offers scant added benefit, while increasing administrative costs.

Importantly, any “essentiality certification” obtained through a pool’s process remains nonbinding; implementers remain free to challenge a patent’s essentiality or validity in court or to refuse a license. The net effect is that formal essentiality checks may do little to streamline or improve licensing outcomes. Instead, they could introduce new procedural hurdles and opportunities for opportunistic delay. If implementers know that every patent must undergo an extra verification step, they may use the process to stall negotiations—disputing essentiality findings or insisting on additional reviews as a tactical matter. This would simply prolong licensing discussions and defer royalty payments, to the detriment of patent holders who have already invested in R&D.

In short, the soft mandate on essentiality checks is, at best, superfluous and at worst a catalyst for holdout behaviour.

C. Undermining Europe’s Innovation Ecosystem

In sum, the draft TTBER Guidelines could inadvertently undermine Europe’s innovation ecosystem and fuel transatlantic tensions. The LNG safe harbour and the expanded essentiality-check provisions echo elements of prior SEP policy initiatives that proved controversial and were ultimately abandoned. By shifting the balance of SEP licensing further in favour of implementers, these proposals risk reducing incentives for patent-driven innovation in Europe.

We therefore urge the Commission to reconsider these aspects of the draft. A more cautious approach—one that refrains from exempting implementer cartels and avoids imposing duplicative patent-checking obligations—would better serve the twin goals of promoting technology transfer and maintaining a vibrant climate for innovation.

II. The Proposed Safe Harbour for Licensing-Negotiation Groups (LNGs)

Section 4.5 of the Draft Guidelines introduces guidance on licensing-negotiation groups (LNGs), which are arrangements whereby a group of potential licensees jointly negotiates license terms with a technology supplier (patent holder or pool). This marks the first time that EU competition guidelines would recognize a safe harbour for such collective negotiations. The Commission’s draft describes possible pro-competitive benefits of LNGs—such as reduced transaction costs, more informed negotiations, or overcoming a “first-mover” disadvantage among implementers.[6]

To qualify for the safe harbour, an LNG would need to satisfy several conditions, including open participation, transparency of rules, a narrow scope limited to joint negotiation, restrictions on information exchange, voluntary membership for both sides, no foreclosure of outside deals, and a cap on aggregate licensing fees (no more than 10% of the product price).[7] In essence, the Commission is proposing to treat LNGs as analogous to patent pools (on the buyers’ side, rather than sellers’ side) by providing a “soft” exemption from Article 101 TFEU, provided these criteria are met.

But this exemption is based on flawed premises. The underlying idea is that implementers face a collective action problem in SEP-licensing negotiations that leads to—the risk that SEP holders demand excessive royalties once implementers are locked into a holdup standard.[8] The Draft Guidelines appear to assume that empowering implementers to negotiate jointly will counteract SEP holders’ supposed bargaining advantage. This premise is unsupported by the evidence.

Both historical experience and empirical research indicate that fears of widespread patent holdup are overstated.[9] Standard-reliant industries (such as wireless communications) have flourished under the current SEP-licensing system, suggesting that the royalty stack and holdup “problem” has not materialized in a systemic way.[10] Notably, a comprehensive study commissioned by the Commission in 2023 found no discernible evidence that patent owners are systematically overcharging implementers or that FRAND disputes are undermining innovation and standard adoption.[11] On the contrary, the study concluded that SEP-licensing frictions have not led to reduced contributions to standards by patent holders, nor a shift by implementers to avoid standardized technologies.[12]

In short, the empirical record does not substantiate the notion of a market failure caused by patent holdup. It would be a dubious policy course to upend long standing licensing norms based on a theory that lacks real-world support.

But crucially, the Draft Guidelines give insufficient weight to the opposite concern of patent “holdout”. Under holdout strategies, implementers strategically avoid or delay taking licenses for SEPs, thereby devaluing those patents and shifting bargaining leverage against innovators.[13] Empowering implementers to form an LNG could exacerbate the risk of holdout. When competitors band together to negotiate, they may collectively agree to stand firm against low royalty offers or prolong negotiations, knowing that the patent holder’s enforcement options (such as injunctions) are constrained once negotiations are ongoing.

Indeed, even supporters of the LNG concept have acknowledged that such groups could be used to coordinate delaying tactics. For example, commentators from the Max Planck Institute observed that, if members of an LNG reserve the ability to pursue bilateral deals after joint talks, they might exploit the joint negotiation to gain information and then drag out individual negotiations, increasing the risk of delay and holdout.[14]

More broadly, competition scholars recognize that collective-purchasing arrangements (which an LNG effectively is) carry inherent dangers. Indeed, they create monopsony power on the buying side and can facilitate explicit or tacit collusion among buyers. An LNG of implementers could enable its members—many of whom may be direct competitors in downstream product markets—to share sensitive information and coordinate licensing strategies, all under the cloak of a nominally pro-competitive joint activity. In other words, LNGs may provide perfect cover for a buyers’ cartel. From an antitrust perspective, a buyers’ cartel is arguably just as pernicious as a sellers’ cartel: it distorts the price (royalty) by artificially suppressing it, which can lead to under-compensation of innovators and underinvestment in future technologies.[15]

Given this, U.S. antitrust authorities have taken a firm view against such collective buyer behaviour. In the context of music licensing, for example, the DOJ filed a statement in litigation explaining that strategies to negotiate rates collectively could amount to per se illegal buyers’ cartels.[16] And as mentioned, a high-ranking DOJ official publicly characterized the Commission’s support for an automotive LNG as “unfortunate”, highlighting a divergence between the EU’s approach and U.S. competition-law norms.[17]

This transatlantic disapproval underscores the gravity of the collusion concerns at stake. The upshot is that collusive behaviour by buyers can stifle competition and harm innovation incentives.

The Commission appears to view LNGs as the mirror image of patent pools, but this analogy is misleading.[18] Patent pools involve cooperation among patent holders who contribute complementary technologies and license them as a package. Because pools can integrate complementary patents and reduce transaction costs, they often produce efficiency gains and are typically pro-competitive (especially when limited to essential patents and governed by FRAND licensing).[19]

By contrast, LNGs are a coalition of technology implementers (patent licensees) coordinating their purchasing of licenses. The competitive dynamics are very different. In a pool, the risk of patent holders engaging in a holdup is mitigated by the pool’s structure (only essential patents, FRAND commitment, etc.), and any attempts to collude on prices above FRAND are checked by the availability of bilateral licensing and the oversight of competition authorities.[20] In an LNG, however, the implementers share the goal of securing lower royalties, and their coordination could simply serve to depress the price below the competitive level.[21]

The Draft Guidelines attempt to import some pool-like safeguards to LNGs (open access, limits on information exchange, etc.), but these may not be sufficient or even apt.[22] For instance, the draft safe harbour would forbid an LNG from engaging in a collective boycott or from penalizing members who enter individual deals. Such conditions, while well-meaning, could prove difficult to police in practice. Any LNG inherently has some degree of group pressure that may discourage members from “defecting” and negotiating separate deals.

Moreover, unlike a patent pool, which is constrained by the inclusion of only essential patents (ensuring the pool’s package has unique value), an LNG has no analogous built-in need for the group’s product; the implementers could always negotiate individually. Thus, an LNG’s chief purpose is to consolidate bargaining power against sellers, which is not a pro-competitive efficiency but an exercise of collective monopsony. In short, the analogy to patent pools does not justify a broad exemption for LNGs, as the economic effects and incentive structures are entirely different.

Another issue is how LNGs would interface with the existing FRAND-licensing framework, particularly as developed under the Huawei v. ZTE line of cases in Europe.[23] The European Court of Justice’s Huawei decision established a balanced negotiation protocol for SEP disputes, defining steps for both SEP holders and implementers to follow in good faith.[24] That framework, which remains the law in the EU, envisions bilateral negotiation and requires that implementers manifest their willingness to take a FRAND license as a condition to avoid injunctions.

Introducing LNGs into this equation raises several problematic legal questions. If implementers negotiate as a group, what does it mean to be a “willing licensee” under Huawei? Can an entire LNG be deemed willing (or unwilling) based on the actions of the group? There is a concern that an implementer could hide behind the group’s collective stance and later claim willingness without ever having engaged individually, as Huawei contemplates. This would make it de facto difficult to impossible for inventors to ever obtain injunctions.

The Draft Guidelines rightly note that any LNG must operate in compliance with Huawei, but it is unclear how that compliance would be ensured in practice. The presence of an LNG could complicate the timeline and exchanges envisioned by Huawei, potentially delaying offers and counteroffers as the group deliberates. In effect, the LNG mechanism might undermine the delicate balance Huawei struck between patent rights and competition law. This is especially troubling, given that the Commission’s now-withdrawn SEP Regulation proposal sought to displace the Huawei framework with new dispute-resolution mechanisms. Many stakeholders—including ICLE’s scholars—opposed this change.[25] Reviving elements of that approach via an LNG safe harbour could be seen as indirectly achieving what the abandoned regulation could not, risking legal uncertainty and renewed controversy in SEP licensing.

In short, absent clear evidence that the benefits outweigh the risks, it is premature to endorse LNGs in guidance. Scholars and industry insiders have already voiced deep reservations about the LNG concept.[26] International alignment is also an issue. Moving ahead unilaterally with an LNG safe harbour could strain relations with key trading partners and enforcement agencies that view such coordination as anticompetitive. It would be ironic and counterproductive if a policy ostensibly aimed at promoting efficient licensing ended up sparking transatlantic frictions and discouraging technology investment in Europe.

To avoid these outcomes, it would be appropriate to withdraw or substantially narrow Section 4.5 in the Draft Guidelines. The existing tools of competition law, applied on a fact-specific basis, are fully capable of assessing any joint negotiation initiatives in the market without the need for a broad safe harbour that would likely be misused.

III. Patent Pools and Essentiality Verification

“Patent pools”—that is, consortia of patent holders who offer combined licenses—can have important pro-competitive benefits. They can reduce transaction costs, prevent royalty stacking, and accelerate the dissemination of technologies—particularly for complex standards that require licensing numerous SEPs.[27] The current Guidelines recognize this by providing a safe harbour for the creation and operation of patent pools, so long as certain conditions are met.[28] Key conditions include that participation in the pool is open to all interested patent holders, that the pool aggregates only essential and complementary patents (with independent experts typically ensuring only truly essential patents are included), that pooled patents are licensed to all comers on FRAND terms, and that members remain free to develop or license competing technology.[29]

These principles have worked well over decades. We have seen several successful pools formed in the telecom, consumer-electronics, and automotive sectors, providing a one-stop licensing solution and helping implementers (especially smaller firms) access critical technologies efficiently. Importantly, the competitive safeguards in pools—FRAND commitments and the focus on complementary (non-substitute) patents—mean that properly structured pools rarely threaten competition. Indeed, the Commission’s own evaluation studies have noted the generally positive impact of pools.[30]

Against this backdrop, the revised Draft Guidelines make several adjustments to the pool safe-harbour criteria aimed at increasing transparency and preventing royalty duplication. In particular, the Draft Guidelines add new recommended requirements that pool administrators: (1) disclose the list of patents (technology rights) included in the pool, (2) disclose the methodology used to verify the essentiality of those patents (as well as the results of any essentiality assessments), and (3) ensure that licensees are not charged twice for the same patent (for example, if they already have a license via a bilateral agreement, they should not pay again through the pool for that patent).[31]

On their face, these suggestions appear designed to address concerns raised by some implementers about transparency in pools. For instance, implementers have sometimes voiced worries about pools including nonessential patents or “double-dipping” by patent owners who license both inside and outside the pool.[32] While the goals of transparency and avoiding double payments are legitimate, there is a risk the essentiality-check requirement may do more harm than good in practice.

First, imposing additional essentiality-verification requirements will increase the costs of forming and maintaining patent pools. Conducting a rigorous essentiality check is an expensive and time-consuming process. It typically involves hiring technical experts to review each patent and determine whether it is actually essential to the standard in question. This expense ultimately must be borne by patent holders (who fund the pool’s operations) and is passed on indirectly in the royalty rates. If the Commission’s guidelines create an expectation that every pool should perform and publish such checks, some patent holders may be deterred from pooling altogether—especially for standards where the number of declared SEPs is very large.

As a result, such assessments must be conducted in a reasonable and practical manner to ensure transparency and accuracy, while avoiding excessive costs that could overburden the system and discourage companies from participating in the standard-setting process. In short, the challenge for policymakers is to design an essentiality-assessment mechanism that is both efficient and effective.[33]

The marginal benefit of formally verifying each patent’s essentiality is doubtful when weighed against these costs. Indeed, many of the most successful pools already include mechanisms to ensure largely essential patents without formalistic checks on every single patent. For example, pools often rely on the patent holders’ own incentives: since non-essential patents have little licensing value (no one needs to license what they don’t infringe), patent owners have limited incentive to contribute blatantly nonessential patents to a pool.

Moreover, if a pool did license nonessential patents, implementers could simply refuse to take a license for those or negotiate a lower rate. There are, therefore, market pressures to keep pools focused on truly essential assets. In practice, some pools do go the extra mile and employ independent evaluators to vet patents (Sisvel and others have done so in certain cases), but that is a choice best left to the pool and its members, who can judge if the benefit outweighs the cost in their context.[34] Mandating or strongly encouraging it across the board, as the draft suggests, imposes a redundant burden.

It is telling that, in other contexts, the Commission has acknowledged how low the average essentiality rate is among declared SEPs; it has been estimate that just 25–40% of declared SEPs are truly essential to a given standard.[35] This means a substantial number of patents would have to be reviewed and found nonessential, a resource-intensive exercise that might not materially improve the licensing environment. The industry already understands that not all declared patents are essential; what matters is that essential ones are available on fair terms. Requiring pools to publicly document this could be seen as solving a transparency issue of which market participants are already aware and that they manage via negotiations.

Second, and perhaps more importantly, an essentiality determination made outside the context of litigation has limited legal or practical value to implementers. Even if a pool announced that its patents have been independently checked and deemed essential, this would not preclude an implementer from later challenging a patent’s essentiality (or validity or infringement) in court. The pool’s determination is not binding on anyone; it is simply a nonauthoritative opinion. Given the significant costs associated with essentiality checks, it would be both unfair and inefficient to render these assessments meaningless by allowing certain implementers to exploit the process merely to delay negotiations or evade royalty payments.[36]

Implementers who are inclined to be sceptical of pool patents will not be meaningfully swayed by the knowledge that an evaluator found them essential; such implementers can still force patent owners to prove essentiality and infringement in court if they choose to litigate. Conversely, if a pool’s evaluator were to label certain patents as not essential, those patents presumably would be left out of the pool license. The patent owner would, however, remain free to assert them outside the pool (if, for instance, they believe the evaluator was mistaken or if the patent is essential to a different implementation not considered).

In short, an essentiality check does not resolve disputes. At best, it provides information that sophisticated parties often already possess or can obtain. Implementers who negotiate licenses (whether through pools or bilaterally) typically have their own internal or external technical analyses of which patents likely read on the standard and their products. The presence of a pool’s essentiality report is unlikely to change those assessments significantly. It might even lead to confusion or false confidence. If an implementer sees a pool’s list of “essential” patents, it may incorrectly assume those are the only patents it needs—when, in fact, other patents (perhaps not in the pool) could also be asserted as essential. Thus, the marginal utility of the proposed transparency measure is questionable.

Third, and most critically from a competition standpoint, making essentiality checks a prominent feature of pooling arrangements could introduce new procedural opportunities for holdout by implementers. For example, the mere availability of a pending essentiality evaluation could be cited as a reason to postpone license negotiations or payments; “let’s wait and see what the evaluator says” becomes a convenient excuse not to sign a deal. If the guidelines strongly encourage pools to perform essentiality checks, implementers may likewise insist on waiting for those results, or challenge the adequacy of the pool’s methodology, as a tactic to defer taking a license.

Additionally, by publishing essentiality findings, pools could inadvertently invite litigation or disputes over those findings. For instance, if a pool’s evaluator deems a particular patent essential, while an implementer disagrees, the implementer might use the discrepancy to argue the pool license is overbroad or to challenge the pool’s fees (claiming they are paying for a nonessential patent). Alternatively, if a patent is deemed nonessential and excluded from the pool, a patent holder might feel aggrieved and choose to assert it separately, leading to parallel negotiations and undermining the pool’s one-stop-shop advantage. In either scenario, the essentiality check can become another locus of contention, fragmenting negotiations instead of streamlining them.

This concern echoes what many stakeholders—including ICLE—noted in response to the Commission’s earlier SEP regulatory initiative: that creating elaborate procedural mechanisms (essentiality assessments, conciliations, etc.) risked becoming a tool for delaying tactics and strategic behaviour by unwilling licensees.[37] It is therefore imperative that competition guidelines not inadvertently endorse similar mechanisms in the context of pools, which have to date functioned relatively well under simpler rules.

Finally, the push for additional essentiality transparency in pools appears to be a solution in search of a problem. The Commission’s own support study for the TTBER evaluation did not identify major competitive problems with existing pool practices.[38] On the contrary, it acknowledged pools’ pro-competitive effects and largely endorsed the current safe-harbour framework.[39] There is no indication of systemic abuse whereby pools are sneakily including large numbers of nonessential patents in order to overcharge implementers. If anything, implementers’ main complaints about pools have been that not all SEP holders join them (leaving some gaps) or that pool royalties still need to be negotiated to cover all patents.[40]

Neither of these issues is solved by forcing more transparency about essentiality. Indeed, adding new burdens could deter the formation of new pools or the expansion of existing ones (if patent owners fear more bureaucracy or potential liability around essentiality representations). That outcome would harm implementers by depriving them of efficient licensing platforms. In short, absent concrete evidence of harm from the status quo, regulators should not saddle pooling arrangements with additional procedural requirements that could upset the delicate balance that makes pools viable.

IV. Conclusion

In short, several of the changes to the TTBER guidelines risk producing adverse outcomes. Creating a safe harbour for licensee cartels (LNGs) would empower coordination that is likely to suppress royalties below competitive levels, discourage patent investment, and invite conflict with our trading partners’ competition authorities. Likewise, inserting cumbersome essentiality-check recommendations into the patent-pool framework would impose new costs and delays that could deter efficient licensing arrangements and be co-opted by implementers intent on holding out.  Rather than improving the licensing landscape, these changes may well tilt it in favour of free riding and disputes.

These initiatives may also exacerbate transatlantic tensions over SEP policy. Indeed, recent commentary from U.S. officials suggests a deep misalignment with the EU on issues like LNGs. Further, U.S. officials have underlined that implementer holdout poses a greater threat to innovation than innovator holdup, particularly because patents are not self-executing rights and a neutral court determination is always required before an injunction can be granted.[41] Moreover, the DOJ has recently emphasized that the mere possession of SEPs cannot give rise to a presumption of market power, nor is antitrust law meant to serve as an over-the-counter remedy for ordinary contract or tort disputes.[42] A prudent course would be to avoid enshrining contentious new principles in the competition guidelines without broader international consensus or clear evidence.

In conclusion, it would be prudent to reconsider the LNG safe harbour and the essentiality-check provisions in the final TTBER Guidelines. The Commission’s overarching mission is to foster innovation, competition, and consumer welfare in the internal market. These goals are best served by a policy that ensures technology creators can obtain a fair return on their investments and that implementers can access new technologies on reasonable terms. A balanced approach—one that rejects collective-holdout tactics and avoids overengineering the patent-licensing process—will encourage both innovation and dissemination.

We believe the existing TTBER framework, with minimal tweaks, largely strikes that balance. Changes that disproportionately advantage one side (implementers) at the expense of the other (innovators) risk undoing years of progress and cooperation in Europe’s standardization ecosystem.

 

[1] Alexander Galetovic, Stephen Haber, & Ross Levine, An Empirical Examination of Patent Holdup, 11 J. Competition L. & Econ. 549 (2015).

[2] Bowman Heiden & Justus Baron, The Economic Impact of Patent Holdout, 38 Harv. J.L. & Tech. 638 (2024); Kirti Gupta & Urška Petrovčič, Evidence of Systematic “Patent Holdout”, 38 Berkeley Tech. L.J. 575 (2023).

[3] Khushita Vasant, EU Guidance on Carmakers’ SEP Licensing “Unfortunate,” US DOJ’s Kallay Says, MLex (10 October 2025), https://www.mlex.com/mlex/amp/articles/2398760.

[4] Communication from the Commission — Guidelines on the Application of Article 101 of the Treaty on the Functioning of the European Union to Technology Transfer Agreements, 2014 O.J. (C 89) 3, § 4.4.1. (hereafter: “the Guidelines”).

[5] Communication from the Commission—Approval of the Content of a Draft for a Commission Regulation on the Application of Article 101(3) of the Treaty on the Functioning of the European Union to Categories of Technology Transfer Agreements and a Draft for Commission Guidelines on the Application of Article 101 of the Treaty to Technology Transfer Agreements, 2025 O.J. (C/2025/5024) (16 September 2025)¶ 285(c). (hereafter: “Draft Guidelines”).

[6] Id. ¶ 300.

[7] Id. ¶ 326.

[8] Mark A. Lemley & Carl Shapiro, Patent Holdup and Royalty Stacking, 85 Tex. L. Rev. 1991 (2007).

[9] Heiden & Baron, supra note 2; Gupta & Petrovčič supra note 2.

[10] Galetovic et al., supra note 1.

[11] Justus Baron, Pere Arqué-Castells, Amandine Léonard, Tim Pohlmann, & Eric Sergheraert, Empirical Assessment of Potential Challenges in SEP Licensing (European Commission 2023).

[12] Id. at 185.

[13] Kalyan Dasgupta & David J. Teece, Protecting Innovation in the Mobile Wireless Ecosystem: Understanding and Addressing “Hold-Out”, 38 Berkeley Tech. L.J. 313 (2023).

[14] Josef Drexl, Beatriz Conde Gallego, & Daria Kim, Position Statement of the Max Planck Institute for Innovation and Competition of 25 April 2025 in the Framework of the Revision of the Technology Transfer Block Exemption Regulation and the Accompanying Guidelines (Max Planck Inst. for Innovation & Competition Research Paper No. 25-10, 2025).

[15] For a more complete discussion of the policy issues that arise applying antitrust to monopsony market position, see, e.g., Geoffrey A. Manne, Brian Albrecht, & Dirk Auer, Labor Monopsony and Antitrust Enforcement: A Distorting Mirror, 74 DePaul L. Rev. 1119 (2025).

[16] Statement of Interest of the United States, Global Music Rights, LLC v. Radio Music License Comm., Inc., No. 2:16-cv-09051-TJH-AS (C.D. Cal. Dec. 5, 2019) (ECF No. 111).

[17] Vasant, supra note 3.

[18] Giuseppe Colangelo, Licensing Negotiation Groups: The New Antitrust Kid on the SEPs Block (2025), https://ssrn.com/abstract=5582774.

[19] Josh Lerner & Jean Tirole, Efficient Patent Pools, 94 Am. Econ. Rev. 691 (2004).

[20] Daniel F. Spulber, Antitrust and Innovation Competition, 11 J. Antitrust Enf’t 5 (2023).

[21] Ruud Peters, Igor Nikolic, & Bowman Heiden, Designing SEP Licensing Negotiation Groups to Reduce Patent Holdout in 5G/IoT Markets, in 5G and Beyond: Intellectual Property and Competition Policy in the Internet of Things 155 (Jonathan M. Barnett & Sean M. O’Connor, eds., 2023).

[22] Draft Guidelines, supra note 5, ¶ 326.

[23] Case C-170/13, Huawei Techs. Co. v. ZTE Corp., ECLI:EU:C:2015:477 (2015).

[24] Id. ¶ 71.

[25] Robin Jacob & Igor Nikolic, Comments Regarding the Draft Regulation on Standard Essential Patents, Int’l Ctr. for Law & Econ. (28 July 2023), available at https://laweconcenter.org/wp-content/uploads/2023/07/ICLE-Comments-to-the-SEP-Regulation.pdf.

[26] See, e.g., Igor Nikolic, Licensing Negotiation Groups for SEPs—Collusive Technology Buyers Arrangements: Pitfalls and Reasonable Alternatives, 56 Les Nouvelles 350 (Dec. 2021); Peters, Nikolic, & Heiden, supra note 21.

[27] Lerner & Tirole, supra note 19.

[28] Guidelines, supra note 4, ¶ 261.

[29] Id.

[30] See, e.g., Baron et al., supra note 11.

[31] Draft Guidelines, supra note 5, ¶ 285.

[32] European Commission, Support Study for the Evaluation of the Technology Transfer Block Exemption Regulation: Final Report 215–30 (Publications Office of the European Union 2024).

[33] Giuseppe Colangelo, Finding an Efficiency-Oriented Approach to Scrutinize the Essentiality of SEPs: A Survey, 18 J. Intell. Prop. L. & Prac. 502 (2023).

[34] Gustav Brismark, Mattia Fogliacco, Carter Eltzroth, Matteo Sabattini, & Richard Vary, Overview of SEPs, FRAND Licensing and Patent Pools, 58 Les Nouvelles 57 (Mar. 2023).

[35] Group of Experts on Licensing & Valuation of Standard Essential Patents (SEPs Expert Group), Contribution to the Debate on SEPs (Jan. 2021), https://ec.europa.eu/docsroom/documents/45217.

[36] Colangelo, supra note 33.

[37] Jacob & Nikolic, supra note 25.

[38] European Commission, supra note 32.

[39] Id.

[40] Id.

[41] Dina Kallay, Keynote at Concurrences Dinner in New York (U.S. Justice Dep’t, 2025), https://www.justice.gov/opa/speech/daag-dina-kallay-delivers-keynote-concurrences-dinner-new-york.

[42] Statement of Interest of the United States, Disney Enters., Inc. v. InterDigital, Inc., No. 1:25-cv-00996-MN (D. Del. 6 October 2025), https://www.justice.gov/atr/media/1416101/dl.

Regulatory Comments

ICLE Comments on Vietnam’s Law on Digital Transformation

We thank the Ministry of Science and Technology of the Socialist Republic of Vietnam for this opportunity to comment on the Law on Digital Transformation . . .

We thank the Ministry of Science and Technology of the Socialist Republic of Vietnam for this opportunity to comment on the Law on Digital Transformation and the future of innovation in Vietnam. The International Center for Law & Economics (ICLE) is a nonprofit, nonpartisan research centre that applies law & economics analysis to technology governance, competition, and consumer-protection policy. Our interest is to ensure that the Law on Digital Transformation advances consumer welfare and innovation through clear, predictable, and proportionate rules grounded in evidence and sound economics.

Vietnam has emerged as one of the most dynamic economies in Southeast Asia, powered by a tech-savvy population, rapid digitalization, an openness to global capital, and a regulatory environment that offers predictability and flexibility. The Law on Digital Transformation, however, threatens to disrupt this balance by creating a chilling effect on innovation that Vietnam can ill afford.

The Law on Digital Transformation’s prescriptive approach seeks to regulate digital markets before harms materialize—ignoring the crucial economic lesson that regulation is costly and should target demonstrable market failures. Vietnam’s existing competition law already provides robust tools to address anticompetitive conduct in both traditional and digital markets, including measures against cartels, abuse of dominance, and merger control. The bill would nonetheless erect a parallel regime focused narrowly on digital companies, introducing the very legal uncertainty that investors and innovators seek to avoid.

These risks are compounded when one considers that digital markets are characterized by dynamic competition—markets defined by innovation, iterative product development, and the constant creation of new consumer value. Companies like Apple, Google, Amazon, Netflix, and OpenAI all illustrate how new entrants can disrupt incumbents by identifying unmet consumer needs. In such markets, rigid, prescriptive rules risk freezing business models in place and stifling innovation.

In this respect, the proposed law’s blanket restrictions fail to distinguish between harmful and pro-competitive behaviour, undermining both incentives for innovation and long-term consumer welfare. The prohibitions on self-preferencing and tying, and the severe limitations on the use of consumer data—all practices that often benefit consumers—illustrate this risk. Each of these measures threatens to tilt the playing field against foreign investors, discourage innovation, and slow digital transformation. Restrictions on data collection, processing, and cross-border transfers, for example, could hinder the delivery of innovative services, disrupt existing business models, and raise compliance costs—all without a clear competitive justification.

Vietnam can look to Europe’s recent experience as a cautionary tale. The European Union’s Digital Markets Act (DMA), which seeks to curb the influence of so-called “gatekeepers,” illustrates the perils of heavy-handed digital regulation. Targeting successful U.S. tech firms while largely ignoring their pro-competitive contributions, the DMA’s restrictions have proven difficult to enforce and have already prompted Apple, Google, and Meta to defer deploying new AI innovations in Europe.

Meanwhile, Europe’s broader economic performance lags that of the United States: private-sector investment is lower, productivity growth is slower, and the region has struggled to produce global technology champions. Replicating this model in Vietnam would risk importing regulatory inefficiency without delivering the promised benefits.

These concerns about the proposed law’s substance are compounded by its procedural and institutional shortcomings. The EU expects to hire as many as 200 additional staff to implement the DMA. The similar Digital Markets, Competition and Consumer Act in the United Kingdom has required quadrupling its regulatory personnel. By contrast, Vietnam’s competition authority is not a legislative body, and expanding its power to dictate broad market rules raises separation-of-powers issues. Moreover, there is currently no public-consultation period scheduled for the Law on Digital Transformation, which means affected companies could have little time to adjust to complex new obligations.

Ultimately, regulation should be a last resort—applied only where markets demonstrably fail and in a manner that preserves incentives for innovation. Vietnam has every reason to nurture its digital economy through targeted, agile measures rather than importing a regulatory experiment whose costs and unintended consequences are already evident elsewhere.

By focusing on a streamlined, evidence-based approach, Vietnam can maintain the openness and predictability that have fuelled its recent success, continue attracting foreign investment, and encourage the dynamic competition that drives innovation and long-term growth. The Law on Digital Transformation risks turning regulation into a blunt instrument, signalling that policymakers are reacting to perceived gaps rather than addressing actual harms.

In the rapidly evolving digital economy, flexibility and evidence-based enforcement of competition law will serve Vietnam far better. Preserving this approach is not only an economic imperative but also a strategic choice: innovation thrives where rules are clear, predictable, and proportionate—not where regulation chokes the very markets it seeks to protect.

Regulatory Comments

ICLE Comments on Section 232 Investigation into PPE, Medical Consumables, and Medical Equipment

I. Introduction The International Center for Law & Economics (ICLE) appreciates this opportunity to comment on the Bureau of Industry and Security’s investigation of the . . .

I. Introduction

The International Center for Law & Economics (ICLE) appreciates this opportunity to comment on the Bureau of Industry and Security’s investigation of the national-security implications of imports of personal protective equipment (PPE), medical consumables, and medical equipment. ICLE is a nonprofit research center that applies economic analysis to questions of law and regulation.

We oppose the application of Section 232 tariffs to medical devices and related products. The United States leads the world in medical-technology innovation and manufacturing, supported by open, rules-based trade with trusted allies. Imports of devices and components complement, rather than displace, U.S. production. Moreover, they are essential to maintain an efficient, resilient, and globally competitive health-care system.

Tariffs would raise costs for hospitals and patients, suppress investment and R&D, and undermine the very innovation that underpins U.S. health-security preparedness. Consistent with Section 232’s statutory purpose, U.S. policy should reinforce the strength of allied supply chains and maintain predictable, cooperative trade relationships that support—not impair—the nation’s medical-technology base.

II. Economic and Public-Health Impacts of Tariffs

Open and competitive trade is the foundation of economic prosperity, especially in innovation-driven sectors like medical technology. When markets are open, firms face competitive pressure to become more efficient, adopt new technologies, and invest in R&D. A broad literature confirms that exposure to global markets drives productivity growth, facilitates technology transfer, and supports sustained U.S. global leadership: the United States controls roughly 40% of the medical-technology (“medtech”) market, while export volumes exceed $141 billion and industry reinvestment in product innovation remains high.[1]

The proposed application of Section 232 tariffs would reverse this dynamic, imposing new costs and instability throughout the medical-technology ecosystem. Modern trade theory emphasizes that comparative advantage evolves dynamically.[2] Access to international markets reshapes domestic capabilities by rewarding sectors that innovate and scale globally. This dynamic interplay between openness and innovation explains why U.S. medtech firms dominate such advanced product segments as imaging, diagnostics, and surgical robotics.

Conversely, barriers like tariffs or quotas impede this evolution, isolating firms from global knowledge flows and eroding long-term competitiveness. Maintaining open, rules-based trade with trusted partners thus strengthens—not threatens—U.S. economic security by reinforcing innovation, efficiency, and resilience in critical health-related industries.

Moreover, imposing tariffs on imports of medical devices, consumables, or related components under Section 232 would increase costs throughout the U.S. health-care system, slow adoption of advanced technologies, and weaken—rather than strengthen—national resilience. Because U.S. health providers operate under fixed reimbursement schedules, any increase in device costs directly translates into higher expenditures for hospitals, insurers, and Medicare, ultimately reducing patient access to life-saving technologies.

A. Tariffs Would Raise Input Costs for Hospitals and Health Systems

Hospitals and health systems already face persistent financial pressure due to inflation, labor shortages, and static Medicare-reimbursement rates. Tariffs would compound these pressures by increasing the cost of imported components and finished products that are integral to medical care. A 2024 analysis found that 82% of health-system executives expected tariff-related import expenses to raise hospital costs by about 15% within six months.[3] Likewise, tariffs on critical supplies are expected to increase costs and reduce availability of key products for hospitals.[4] These higher input prices are not absorbed by manufacturers alone; they are passed through the supply chain and ultimately borne by hospitals, private insurers, and federal programs like Medicare and Medicaid.

During prior rounds of Section 301 tariffs on Chinese medical imports, manufacturers and distributors in the medical-device sector reported cost pressures on various device components and subassemblies—such as electronics, sensors, housings, and tubing—especially for diagnostic, monitoring, and surgical devices.[5] This experience illustrates that trade restrictions intended to promote domestic production often have the opposite effect in highly integrated industries—eroding competitiveness and diminishing capacity for innovation.

B. Tariffs Would Raise Consumer Prices and Delay Adoption of Advanced Medical Technologies

Medical devices are capital-intensive goods with long procurement cycles and complex regulatory-approval requirements. When hospitals anticipate higher import prices or uncertain supply, they may postpone or cancel equipment upgrades. Tariffs on medical products would likely further strain an already fragile health-care supply chain, driving up costs and reducing the availability of essential medical devices and equipment.[6] Similarly, medtech manufacturers anticipate a combined tariff impact of more than $2 billion across 2024-2025, forcing many firms to reduce production and defer new-product launches.[7] As device upgrades are delayed, hospitals must continue using older, less-efficient technologies—directly undermining the goal of a modern and resilient health-care infrastructure.

Moreover, while a few multinational firms maintain relatively high returns, the medical-device sector actually operates on narrow effective margins, once research, compliance, and capital costs are included. Large device companies typically have profit margins of 20-30%.[8] Yet industry data suggest that the medical equipment and supplies sector on the whole now reports net margins in the upper single digits, with operating margins near 10%.[9] Recent financial benchmarking indicates that smaller and mid-sized medical-device manufacturers—firms responsible for much of the industry’s innovation—operate with earnings before interest and taxes (EBIT) of roughly 4.6% of their revenues, reflecting the sector’s tight margins relative to larger diversified medtech companies.[10] When margins are this thin, tariff costs cannot be easily absorbed; they are inevitably passed through, in large part, to hospitals and consumers in the form of higher prices.

Reduced profitability and policy uncertainty also discourage R&D investment. Industry analysis illustrates that medtech profitability has declined globally in recent years, with average operating income falling by roughly three percentage points, as inflation, supply-chain disruptions, and regulatory costs have all increased.[11] Additional tariff-driven cost increases would intensify this compression, leaving fewer resources for R&D and compliance.

And while medtech firms often enjoy healthy gross margins, those margins are critical to funding ongoing innovation. When those margins erode, firms lose the flexibility to reinvest in R&D, slowing the pace of new-product development.[12] Tariffs will shrink both the gross margins and the net margins, driving further retrenchment and depressing institutional capacity to invest in R&D.

The combined effect of higher import prices, reduced investment, and delayed innovation would therefore be fewer new medical technologies entering the U.S. market and slower replacement of aging equipment. In the long term, these consequences would erode the resilience of the U.S. health-care system—the very objective that these Section 232 investigations seek to secure.

C. Trade-Policy Uncertainty and Investment in Medical Technology

Even before tariffs take effect, the uncertainty surrounding their potential imposition can suppress investment and innovation in the medical-technology sector. Economists have long observed that volatility in trade policy leads firms to postpone or cancel capital expenditures and R&D, a dynamic known as the “real options” effect. When future input costs or market-access rules are unclear, it becomes rational for companies to delay irreversible investments until policy direction stabilizes. The cumulative effect across the industry is lower aggregate investment, slower entry into new markets, and diminished innovation.[13]

Empirical studies of the 2018–2019 trade-tension period found that a one-standard-deviation rise in trade-policy uncertainty reduced U.S. manufacturing investment by roughly 1–2% over the following year, independent of what actual tariff levels were imposed.[14] For innovation-intensive industries like medtech—where R&D costs typically take up 8% of annual revenues[15]—policy instability can translate quickly into deferred product development and delayed regulatory submissions. Firms facing uncertainty about tariff coverage, reimbursement effects, or retaliatory measures have strong incentives to redirect resources toward short-term operations, rather than long-term innovation.

Stable and predictable trade rules therefore constitute a precondition for maintaining U.S. technological leadership in medical devices. A tariff-driven environment characterized by periodic investigations and changing duty rates not only raises costs directly, but also magnifies uncertainty, depressing forward-looking investment across the supply chain. In this sense, trade-policy volatility functions as a hidden tax on innovation. A consistent, rules-based approach to international medical-device trade, anchored in transparency and allied cooperation, would better support the long-term competitiveness and national-security resilience of the U.S. medtech industry.

D. Tariffs on PPE Are an Inappropriate Economic Tool to Promote Reshoring

Importantly, Section 232 authority was designed to address genuine national-security threats from adversarial sources, not to penalize allied trade. Historically, successful 232 actions have targeted steel, aluminum, or critical minerals dominated by non-allied producers.[16] Applying this national-security tool to medical devices imported chiefly from NATO and USMCA partners would be inconsistent with both statutory intent and economic logic.[17] As the Bureau of Industry and Security has noted, the statute’s purpose is to mitigate “whether the importation of the article in question is in such quantities or under such circumstances as to threaten to impair the national security,” not to disrupt allied cooperation essential to public health.[18]

Further, medical-device manufacturing is inherently capital intensive and heavily regulated by the U.S. Food and Drugs Administration (FDA). Under 21 C.F.R. Part 820, manufacturers must validate every production line and supplier, with significant documentation and preapproval requirements for any process change.[19]

Although a tariff shock might be intended to spur reshoring, firms must in practice incur significant sunk costs and time to requalify suppliers and production processes. In the medical-device sector, supplier requalification itself often takes months, and includes mandatory audits, capability studies, quality-agreement updates, and validation under regulatory frameworks like 21 C.F.R. § 820.[20] Because many changes may require full validation of process and materials, the short-term shift in capacity is highly constrained and may lead to disruptions or shortages before any new domestic capacity becomes viable.

In short, Section 232 tariffs on medical devices and PPE would misidentify the source of risk. They would penalize integrated trade with close allies, undermine established regulatory and manufacturing networks, and inflict economic harm on precisely the industries that anchor U.S. health-security resilience.

III. The U.S. Medical Technology Industry: A Global Leader

Given the foregoing description of the economics of the medtech industry, it is worth asking why this sector—long a cornerstone of U.S. innovation and export strength—should be viewed as a national-security vulnerability at all. The United States is the undisputed global leader in medical-technology innovation and manufacturing. Indeed, U.S. companies account for roughly 40% of worldwide medical-device production, by far the largest share of any country.[21]

The medtech sector is defined by high-value, research-intensive manufacturing. The industry consistently reinvests around 7–8% of revenues into R&D, ranking among the highest R&D intensities in manufacturing.[22] This robust innovation ecosystem—fueled by leading research universities, deep venture-capital markets, and strong intellectual-property protections—drives continual advances in imaging equipment, in-vitro diagnostics, surgical robotics, and implantable devices. For example, U.S. firms are at the forefront of MRI and CT imaging technology, next-generation glucose monitors and diagnostic assays, robotic-assisted surgical systems, and artificial joints and stents, among many other cutting-edge products.[23]

The industry’s emphasis on innovation not only saves lives but also supports a high-skill domestic workforce: approximately 500,000 workers are employed directly in the U.S. medical-device-manufacturing industry, with total direct and indirect employment approaching 2 million.[24]

U.S. medtech firms are also vigorous exporters. The United States exported more than $100 billion in medical devices and related equipment in 2023.[25] Even in key product categories where global competition is intense, American firms excel. In earlier years, the United States achieved net export surpluses in high-value device categories such as diagnostic imaging and orthopedics. [26] Although more recent trade data show changes in the balance, the United States remains a leading global exporter in those segments.[27] These high-end devices—often produced by U.S. companies at home or in close trade-partner countries—compete on quality and innovation, rather than low cost.

In sum, the U.S. medtech industry’s global leadership is built on innovation, skilled employment, and export success. These factors underscore that America’s medical-device-manufacturing base is strong and globally competitive, a foundation for national health security that open trade further reinforces.

A. Allied Trade Relationships and Balanced Flows

The U.S. medical technology industry is deeply integrated into reciprocal trade relationships with allied economies, resulting in balanced flows of devices and components. America’s major trading partners for medical devices are not adversaries, but close allies: Europe (especially Germany, Ireland, and the Netherlands), Canada, Mexico, Japan, South Korea, and Singapore are both among the top sources of U.S. medtech imports and major destinations for U.S. exports.

In 2018, for example, the United States exported more than $20 billion in medical devices to the EU, which has historically accounted for nearly 40% of U.S. device exports.[28] Import data show that the European Union is also an important supplier of U.S. medical instruments. In 2023, it contributed roughly $11.5 billion of $19.5 billion in U.S. imports in that device category (roughly 59%).[29]

Meanwhile, North American partners—especially Canada and Mexico—play significant roles as regional suppliers and exporters in complementary device segments.[30] U.S.–Mexico trade in medical devices is largely balanced and complementary. In recent years, Mexico has been the leading supplier of U.S. medical-device imports, accounting for roughly 17% of total import value—mainly lower-technology products such as disposables and surgical instruments produced through cross-border manufacturing.[31]

Canada is also both a significant market and supplier in U.S. medical-device trade. Exports of medical equipment, supplies, and control instruments from Canada to the United States exceeded $6.8 billion in 2024.[32] Meanwhile, in 2024, Canada’s medical-device imports from the United States were C$5.9 billion, representing about 42% of Canada’s total medtech imports.[33]

In Asia, Japan and South Korea both purchase high-value U.S. devices (for example, Japanese hospitals import American orthopedic implants and diagnostic instruments), even as companies in those countries supply the United States with specialized components like optical lenses and semiconductor parts for medical equipment.[34]

These trade relationships are characterized by a two-way flow of goods: U.S. companies export complex finished devices and receive in return a range of inputs, subassemblies, and some finished products from allied nations. Importantly, imports from China constitute only a relatively small fraction of U.S. medtech imports (roughly 10% in recent years) and that share has been declining as U.S. sourcing diversifies toward allied suppliers.[35]

The evidence suggests a supply-chain strategy centered on trusted partners. The reciprocity and balance in these trade flows demonstrate that imports are largely coming from friends, and U.S. firms are succeeding in selling globally. Far from one-sided dependence, U.S. medtech trade with allies strengthens all parties.

B. Imports’ Role in Meeting U.S. Health-Care Demand

The COVID-19 pandemic offered a stark illustration of the importance of global supply networks in meeting surges in health-care demand. In normal times, imports fill critical gaps in the U.S. health system’s needs for medical devices and supplies, especially for specialized or lower-volume products that are not efficient to manufacture domestically at scale.

During the height of the pandemic, the United States leveraged imports from allies to rapidly scale up life-saving equipment. A prominent example was the surge in ventilator production in 2020: even as American manufacturers like General Motors and ventilator companies retooled to assemble ventilators domestically, they depended on imported inputs (valves, sensors, oxygen concentrators, etc.) from partner countries to boost output. According to contemporary analyses, the only feasible way to meet the unprecedented 500–1,000% increase in ventilator demand was to “supercharge ventilator makers’ global production capacities” by pooling resources across borders, rather than attempting total self-reliance.[36]

For example, Medtronic’s Ireland-based ventilator manufacturing facility reportedly ramped up production, reallocating staff and expanding shift coverage to supply global demand.[37] More broadly, European manufacturers took coordinated steps to bolster ventilator-component supply chains across countries.[38] Similarly, COVID-19 diagnostic test kits were produced through transnational cooperation, with U.S. labs relying on reagents and chemicals from allies (and vice versa) to scale up testing quickly.[39]

In short, imports function as both a safety valve and a source of resilience for U.S. health care; they ensure that American patients and doctors have timely access to every medical tool needed, especially when domestic production alone cannot immediately meet a spike in demand.

C. Resilience Through Diversification, Not Isolation

Policymakers increasingly recognize that supply-chain resilience in medical technology comes from diversification across trusted partners, rather than from attempting an autarkic approach. Empirical research on the recent supply disruptions demonstrates that geographic concentration of production is the primary vulnerability—for instance, overreliance on a single country or region for a critical component can create a choke point—whereas maintaining “safe openness” through a broad network of suppliers reduces risk.[40] Resilient medical supply chains depend on broad, cross-border diversification with built-in redundancies that allow production to adjust rapidly in response to shocks or disruptions.[41] In the medical-device sector, both industry and government have moved to implement this lesson.

U.S. and European manufacturers are increasingly coordinating to establish redundant production capacity for critical products. For example, U.S. medtech OEMs maintain production sites abroad to enable geographic flexibility in manufacturing.[42] Some have explicitly expanded manufacturing operations in Singapore and Southeast Asia, enabling them to shift production among locations in response to demand or disruption.[43] Major medtech firms from the United States, EU, and Japan also frequently rely on one another’s components, creating inherent redundancies—if one source goes offline, alternative sources in another allied nation can fill the gap.[44]

Such collaborative redundancy is bolstered by reciprocal regulatory recognition initiatives among allies. A salient case is the Medical Device Single Audit Program (MDSAP), which pledges the FDA and regulators in Canada, Japan, Australia, and other jurisdictions to accept a single standardized quality audit of a device manufacturer.[45] Programs like MDSAP streamline compliance across countries, enabling companies to shift production or substitute suppliers rapidly across jurisdictions without regulatory delay. Likewise, international regulatory guidance—such as the International Medical Device Regulators Forum’s (IMDRF) medical-device cybersecurity framework—explicitly aims for convergence of cybersecurity principles and practices across jurisdictions to preserve device functionality and patient safety, thereby enabling mutual reliance on allied medical products in emergencies.[46]

Crucially, embracing imports from a diverse set of allied economies enhances U.S. preparedness. A strong consensus has emerged that attempting to localize entire supply chains domestically would undermine resilience by cutting off access to alternative sources. A 2024 OECD report, for example, found that shortages in critical medical goods were best addressed by maintaining multiple sourcing options across different countries—smoothing potential disruptions.[47] Diversified global supply networks tend to recover faster from shocks than isolated national chains.[48] Similarly, countries with more trade partners had fewer medical supply shortages during COVID-19, whereas those dependent on one foreign source or solely on domestic production faced greater scarcity.[49]

The medtech sector’s own experience confirms that open, allied trade is a strength. The U.S. medical technology base is robust, in large part, due to its global links. Diversified sourcing enables “a consistent response to external stressors” and prevents overreliance on any single market or supplier.[50] In short, maintaining and expanding imports from trusted allies is not a strategic liability but a strategic asset for the United States. It builds redundancy, ensures access to lifesaving technologies not made at home, and grants flexibility to manage crises. In the face of pandemics and other disruptions, a diverse allied supply chain is America’s first line of defense, whereas protectionism and concentration would only foment greater fragility.

IV. Conclusion

The U.S. medtech sector is a pillar of both economic strength and national health security. Its global leadership depends on openness, stability, and collaboration with trusted trade partners. Section 232 tariffs on medical devices or PPE would erode these advantages—raising costs, amplifying uncertainty, and diverting resources away from the research and innovation that safeguard public health.

Rather than broad trade restrictions, national-security policy should focus on targeted, evidence-based measures that address specific vulnerabilities, while preserving the benefits of allied integration. A predictable, rules-based trade environment is essential to maintain U.S. competitiveness, investment, and readiness in critical medical technologies.

Accordingly, ICLE urges the U.S. Commerce Department to reject the use of Section 232 tariffs in this proceeding and to reaffirm that open, cooperative trade among allies is an asset to U.S. security—not a threat to it.

[1] See Medical Technology Industry, U.S. Int’l Trade Admin. SelectUSA, https://www.trade.gov/selectusa-medical-technology-industry (last visited Oct. 15, 2025); see also Medical Technologies, U.S. Int’l Trade Admin., https://www.trade.gov/medical-technologies-0 (last visited Oct. 15, 2025).

[2] See infra Section III.

[3] Sunit Patel & Rupert Watson, The Impact of Tariffs on Healthcare Costs, Mercer (Apr. 10, 2025), https://www.mercer.com/en-us/insights/us-health-news/the-impact-of-tariffs-on-healthcare-costs.

[4] Tina Freese Decker, Tariff Implications for American Health Care, AHA News (May 19, 2025), https://www.aha.org/news/chairpersons-file/2025-05-19-tariff-implications-american-health-care.

[5] See, e.g., Analysis of Section 301 Tariff Impacts on Electromedical Devices, Wash. Int’l Trade Ass’n (2022), available at https://www.wita.org/wp-content/uploads/2022/08/CTA_Section-301-Tariff-Whitepaper.pdf; see also The Hidden Risks of Tariffs in Medical Device Supply Chains, Everstream Anal., https://www.everstream.ai/articles/hidden-risk-tariffs-medical-devices (last visited Oct. 16, 2025).

[6] Robert M. Orfaly, Tariffs May Strain the Fragile Healthcare Supply Chain, AAOS Now (May 29, 2025), https://www.aaos.org/aaosnow/2025/may/commentary/commentary01.

[7] Susan Kelly, Cost Cuts, Production Shifts: How MedTech Firms Are Managing Tariffs, MedTech Dive (May 22, 2025), https://www.medtechdive.com/news/medtech-Q1-earnings-tariffs-impact/748794.

[8] An Overview of the Medical Device Industry (Ch. 7), in Report to the Congress: Medicare and the Health Care Delivery System, Medicare Payment Advis. Comm’n (Jun. 2017), available at https://www.medpac.gov/wp-content/uploads/import_data/scrape_files/docs/default-source/reports/jun17_ch7.pdf.

[9] Medical Equipment & Supplies Industry Profitability Ratios, CSIMarket, https://csimarket.com/Industry/industry_Profitability_Ratios.php?ind=804 (last visited Oct. 15, 2025).

[10] Medical Device Manufacturing: Industry M&A Trends, Valuation, and Financial Performance, InvestmentBank.com (Jun. 22, 2025), https://investmentbank.com/insights/medical-device-industry.

[11] Global MedTech 2023 – Stem the Tide, Roland Berger (2023), available at https://content.rolandberger.com/hubfs/07_presse/Global_MedTech_2023.pdf.

[12] See id.; See also Pulse of the MedTech Industry Report 2025, EY Insights (2025), available at https://www.ey.com/content/dam/ey-unified-site/ey-com/en-gl/industries/life-sciences/documents/ey-gl-medtech-pulse-report-09-2025.pdf.

[13] See, generally, Dario Caldara et al., The Economic Effects of Trade Policy Uncertainty, 109 J. Monetary Econ. 38 (2020), available at https://www.federalreserve.gov/econres/ifdp/files/ifdp1256.pdf; see also Kyle Handley & Nuno Limão, Trade Policy Uncertainty, 14 Ann. Rev. Econ. 363 (2022), available at https://www.nber.org/papers/w29672.

[14] Id.

[15] Richard Bartlett et al., Medtech Pulse: Thriving in the Next Decade, McKinsey & Co. (Sep. 2023), available at https://www.mckinsey.com/~/media/mckinsey/industries/life%20sciences/our%20insights/medtech%20pulse%20thriving%20in%20the%20next%20decade/medtech-pulse-thriving-in-the-next-decade.pdf; Innovation — The European Medical Technology in Figures, MedTech Europe, https://www.medtecheurope.org/datahub/innovation (last visited Oct. 15, 2025).

[16] Section 232 Investigations: Overview and Issues for Congress, Cong. Res. Svc. (2021), available at https://www.congress.gov/crs_external_products/R/PDF/R45249/R45249.35.pdf; Scott Lincicome & Inu Manak, Protectionism or National Security? The Use and Abuse of Section 232, Policy Analysis No. 912, Cato Inst. (2021), https://www.cato.org/policy-analysis/protectionism-or-national-security-use-abuse-section-232.

[17]  19 U.S.C. § 1862; see also Section 232 Investigations Program, U.S. Dep’t of Commerce Bure. of Ind. & Sec., https://www.bis.doc.gov/232 (last visited Oct. 15, 2025).

[18] Id.

[19] 21 C.F.R. § 820 (2025).

[20] See Ben Bancroft, Ultimate Guide to Supplier Management for Medical Device Companies, Greenlight Guru (Nov. 8, 2023), https://www.greenlight.guru/blog/supplier-management-medical-device; Medical Device Supplier Management: Definition, Requirements, and Process, SimplerQMS (Aug. 11, 2025), https://simplerqms.com/medical-device-supplier-management; Quality System Regulation: Process Validation, U.S. Food & Drug Admin. (2015), available at https://www.fda.gov/media/94074/download.

[21] See Medical Technologies, U.S. Int’l Trade Admin., https://www.trade.gov/medical-technologies-0 (last visited Oct. 15, 2025); see also Medical Device Industry Facts, AdvaMed, https://www.advamed.org/medical-device-industry-facts (last visited Oct. 15, 2025).

[22] Facts & Figures 2024, MedTech Europe (Jul. 2024), available at https://www.medtecheurope.org/wp-content/uploads/2024/07/medtech-europe–facts-figures-2024.pdf.

[23] See, e.g., Scott Whitaker, Testimony Before the U.S. Senate Committee on Finance, AdvaMed (May 14, 2025), at 1, https://www.advamed.org/industry-updates/news/advamed-testifies-in-u-s-senate.

[24] SelectUSA: Medical Technology Industry, U.S. Int’l Trade Admin., https://www.trade.gov/selectusa-medical-technology-industry (last visited Oct. 15, 2025).

[25] Id.

[26] Medical Devices and Equipment: Competitive Conditions, U.S. Int’l Trade Comm’n (2006), at 4, available at https://www.usitc.gov/publications/332/pub3909.pdf.

[27] U.S. Medical Devices: Imports and Exports, the Role of Tariffs and the FDA, Fla. Int’l. Med. Expo (2020), available at https://www.fimeshow.com/content/dam/Informa/fimeshow/en/downloads/FIME20-US-medical-device-report-eng.pdf.

[28] Healthcare Resource Guide – European Union, U.S. Int’l Trade Admin., https://www.trade.gov/healthcare-resource-guide-european-union; Brian Daigle & Mihir Torsekar, The EU Medical Device Regulation and the U.S. Medical Device Industry, J. Int’l Commerce & Econ. (Nov. 2019), available at https://www.usitc.gov/publications/332/journals/eu_medical_device_regulation_us_medical_device_industry.pdf.

[29] Instruments and Appliances Used in Medical or Veterinary Sciences: 2023 Imports by Country (HS 901890), World Bank, https://wits.worldbank.org/trade/comtrade/en/country/ALL/year/2023/tradeflow/Imports/partner/WLD/product/901890 (last visited Oct. 15, 2025).

[30] Country Commercial Guide: Canada — Medical Devices, U.S. Int’l Trade Admin., https://www.trade.gov/country-commercial-guides/canada-medical-devices (last visited Oct. 15, 2025).

[31] See FIME, supra note 28.

[32] See Hessam Mehrabi & Rambod Behboodi, The Evolving Tariff Threat: Impact on Med-Tech and Life Science Industries, Borden Ladner Gervais LLP (Feb. 27, 2025), https://www.blg.com/en/insights/2025/02/the-evolving-tariff-threat-impact-on-med-tech-and-life-science-industries.

[33] See Medical Devices: Industry Profile, Innov., Sci. & Econ. Dev. Can., https://ised-isde.canada.ca/site/canadian-life-science-industries/en/medical-devices/industry-profile (last visited Oct. 15, 2025).

[34] See Country Commercial Guide: South Korea — Medical Equipment and Devices, U.S. Int’l Trade Admin., https://www.trade.gov/country-commercial-guides/south-korea-medical-equipment-and-devices (last visited Oct. 15, 2025).

[35] See CGlobalization of U.S. Medical Product Supply Chains, in Medical Product Access and Innovation, Nat’l Acads. Press (2021), https://www.ncbi.nlm.nih.gov/books/NBK583730.

[36] COVID-19 Ventilator Shortage: Manufacturing Solution, World Econ. Forum (2020), https://www.weforum.org/stories/2020/04/covid-19-ventilator-shortage-manufacturing-solution.

[37] Ventilator Manufacturer Ramps Up Production Amid Coronavirus Crisis, 24×7Mag (Mar. 22, 2020), https://24x7mag.com/medical-equipment/patient-care-equipment/ventilators/ventilator-manufacturer-ramps-production-coronavirus-crisis.

[38] One Crisis, Different Paths to Supply Resilience, Nat’l Lib. of Med. (2022), https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9705261.

[39] Samuel M. Goodman, COVID-19 Testing Supplies One Year into the Pandemic (USITC Working Paper ID-21-076,  2021), available at https://www.usitc.gov/publications/332/working_papers/wp_id_21_076_covid-19_testing_supplies_compiled_052121-compliant.pdf.

[40] Richard Baldwin & Rebecca Freeman, Risks and Global Supply Chains: What We Know and What We Need to Know (NBER Working Paper No. 29444, 2021), available at https://www.nber.org/system/files/working_papers/w29444/w29444.pdf.

[41] Susan Lund, Building National Supply Chain Resilience, McKinsey Glob. Inst. (Jul. 11, 2021), https://www.mckinsey.com/mgi/media-center/building-national-supply-chain-resilience.

[42] See The 2024 Global Medtech Contract Manufacturing Report, Alira Health (Feb. 2024), available at https://alirahealth.com/wp-content/uploads/The-2024-Global-Medtech-Contract-Manufacturing-Report.pdf.

[43]  See Medtech CDMOs in Southeast Asia: Landscape Overview and Investment Opportunities, L.E.K. Consult. (Jun. 17, 2025), available at https://www.lek.com/sites/default/files/insights/pdf-attachments/medtech-cdmos-sea.pdf; What Makes Singapore the Best Hub in Asia for MedTech Manufacturing, Sing. Econ. Dev. Bd. (Nov. 11, 2024), https://www.edb.gov.sg/en/business-insights/insights/what-makes-singapore-the-best-hub-in-asia-for-medtech-manufacturing.html.

[44] See Decoding Tariff Volatility: How MedTech Must Remodel for Resilience, Kearney (Jul. 30. 2025), https://www.kearney.com/industry/health/article/decoding-tariff-volatility-how-medtech-must-remodel-for-resilience.

[45] See MDSAP: Purpose, Structure & Participating Authorities, Med. Dev. Sngl. Audit Program, https://www.mdsap.global (last visited Oct. 15, 2025).

[46] Principles and Practices for Medical Device Cybersecurity, Int’l. Med. Dev. Regulators Forum (Mar. 18, 2020), available at https://www.imdrf.org/sites/default/files/docs/imdrf/final/technical/imdrf-tech-200318-pp-mdc-n60.pdf.

[47] Securing Medical Supply Chains in a Post-Pandemic World, OECD (2024), https://www.oecd.org/en/publications/2024/02/securing-medical-supply-chains-in-a-post-pandemic-world_3c8cef7c.html.

[48] See, e.g., Laura Lebastard, Marco Matani, & Roberta Serafini, Understanding the Impact of COVID-19 Supply Disruptions on Exporters in Global Value Chains, CEPR/VoxEU (Mar. 24, 2023), https://cepr.org/voxeu/columns/understanding-impact-covid-19-supply-disruptions-exporters-global-value-chains.

[49] Id.

[50] Building Supply Chain Resilience: White Paper, AdvaMed (2023), available at https://www.advamed.org/wp-content/uploads/2023/06/Building-Supply-Chain-Resilience-White-Paper-final.pdf.

Regulatory Comments

ICLE Comments on the European Commission Digital Omnibus

Introduction We thank the European Commission for launching this call for evidence on the forthcoming Digital Omnibus to simplify EU rules on data, cybersecurity, and . . .

Introduction

We thank the European Commission for launching this call for evidence on the forthcoming Digital Omnibus to simplify EU rules on data, cybersecurity, and artificial intelligence. ICLE is a nonprofit, nonpartisan research centre that applies law & economics analysis to technology governance, competition, and consumer-protection policy. Our interest is to ensure that the EU’s digital rulebook advances consumer welfare and innovation through clear, predictable, and proportionate rules grounded in evidence and sound economics.

In this submission, we highlight the aspects of the Digital Omnibus proposal that we consider particularly worthy of support (Section I).

In Section II, we comment on the General Data Protection Regulation (GDPR), the key element of the EU digital acquis in need for reform, but which is not mentioned in the consultation document.

Given our mission to apply law & economics analysis, in Section III, we comment on the methodology to identify simplification priorities. As an example, we focus on the importance of taking seriously the impacts of policy choices on business users. Reform initiatives that fail to do so are likely to fall short in addressing numerous significant barriers to innovation and economic growth posed by EU law.

I. Executive Summary

A. Supported Digital Omnibus Proposals

  • ePrivacy Directive Reform: Remove Article 5(3) cookie provisions and rely on the GDPR’s more flexible framework, eliminating duplicative requirements and the overly restrictive binary-consent model that lacks “legitimate interest” provisions.
  • Cybersecurity Reporting: Streamline overlapping incident-reporting obligations across the AI Act, GDPR, NIS2 Directive and other frameworks in order to reduce redundant reporting burdens.
  • AI Act Implementation: Ensure proportionate enforcement that balances innovation needs with compliance, particularly for startups whose resources may be diverted from development.

B. GDPR Simplification

  • The consultation omits GDPR reform, despite the Commission’s commitment to assess the digital acquis; this represents a missed opportunity for meaningful simplification.
  • The core problem is not the GDPR’s text, but its enforcement structure, which fosters privacy absolutism by enabling data-protection authorities (DPAs) to act as both prosecutor and judge with near-limitless discretion.
  • Current enforcement treats privacy as supreme over all other EU objectives, contradicting both the GDPR’s own proportionality principles and broader EU economic goals.
  • Proposed solutions include embedding proportionality in the main GDPR text and establishing multidisciplinary tribunals not entirely composed of privacy lawyers, in order to balance competing rights and economic realities.

C. Methodological Concerns About Identifying Simplification Targets

  • Simplification efforts must consider significant indirect effects, including how restrictions on digital platforms harm their business users.
  • Examples of overlooked impacts:
    • DMA enforcement against Meta degrading advertising tools without analysing damage to EU business advertisers.
    • Political advertising shutdown by major platforms due to unclear EU rules.
    • 30% traffic drop for EU hotels after DMA enforcement on Google, benefiting large U.S. travel agencies instead.
  • Current impact assessments fail to capture these significant indirect barriers to EU innovation and economic growth.
  • This should lead to careful analysis of indirect negative effects of the EU digital acquis, including asymmetric regulations (DMA, DSA).

II. The Digital Omnibus Proposals

A. ‘Rules on cookies and other tracking technologies laid down by the ePrivacy Directive’

We agree with the Commission that the provisions of the ePrivacy Directive on cookies and technologies used for similar purposes are outdated. A pragmatic solution would be to remove those provisions (in particular, Article 5(3) of the ePrivacy Directive) and rely on the more flexible data-protection framework from the GDPR.

The current interpretation of Article 5(3) has evolved far beyond its original scope, as evidenced by recent European Data Protection Board (EDPB) guidelines that would require consent for URL and pixel tracking, IP-based tracking, certain forms of “local processing” once information (or its derivatives) leaves the device, and other mechanisms such as headers or authentication tokens.[1] This expansive interpretation effectively treats any information exchange between a user device and a server as requiring prior consent, with only two extremely narrow exceptions: transmission of communications and services “strictly necessary” for explicitly requested functions.

Unlike the GDPR, the ePrivacy Directive offers no “legitimate interest” basis for processing, forcing businesses into a binary choice between obtaining consent or fitting within increasingly narrowly interpreted technical-necessity exceptions. This rigid framework fails to recognize that certain processing activities—such as basic analytics or funding mechanisms for free services—may be essential for sustainable service provision, even if they do not fit a very narrow interpretation of technical necessity.

The disconnect between the restrictive approach embodied by many DPAs’ interpretation of the ePrivacy Directive and the GDPR’s more nuanced framework creates legal uncertainty and compliance burdens, without clear privacy benefits.

When authorities interpret “necessity” to exclude economic or business necessities, such as revenue generation, they effectively undermine sustainable business models upon which European consumers may rely. This is particularly problematic for SMEs and startups that depend on standard web analytics and advertising technologies to compete effectively in digital markets.

Rather than attempt to implement further patchwork fixes to these outdated provisions, the Commission should recognize that the GDPR already provides comprehensive data-protection rules with appropriate balancing mechanisms. Removing Article 5(3) and related provisions would eliminate duplicative requirements, while maintaining strong privacy protections through the GDPR’s more sophisticated and flexible framework.

If full repeal is not feasible, the Omnibus could nonetheless narrow the gap by codifying clear exemptions for analytics, security/fraud prevention, and basic service-quality measurement. Moreover, it would be advisable to align “necessity” under the ePrivacy Directive with the GDPR’s proportional, risk-based view of necessity. But the principled solution remains to remove Article 5(3) and govern these practices under the GDPR.

B. ‘Cybersecurity related incident reporting obligations’

We welcome the proposal to streamline overlapping horizontal and sector-specific obligations and reporting tools in order to minimise reporting burden. Under the AI Act, the GDPR, the NIS2 Directive, and multiple other legal frameworks, businesses and other institutions may face separate duties to report the same incident in differing ways.

C. ‘The smooth application of the AI Act rules’

The rush to regulate artificial intelligence in the EU—combined with last-minute changes to the legislative proposals made in response to ChatGPT’s emerging market success—resulted in legislation (the AI Act) that may significantly hamper the EU’s adoption of these pivotal technologies. As we noted in our work on tech startups, compliance with the AI Act may divert significant resources from startups and stifle their development.[2]

It is thus important to ensure that the AI Act’s provisions are enforced proportionately. This must include a careful evaluation of any guidelines and other documents meant to implement the law. AI Act implementation efforts to date, including drafting of the General Purpose AI Code of Practice, have not treated AI’s potential to improve European economic welfare with sufficient seriousness.

III. GDPR Simplification

In the communication on “A Simpler and Faster Europe”, the Commission refers to “the broader assessment, during the first year of the mandate, of whether the expanded digital acquis adequately reflects the needs and constraints of businesses such as SMEs and small midcaps, going beyond necessary guidance and standards that facilitate compliance”.[3] While the Commission listed the GDPR among the digital acquis that would be subject to assessment, the Digital Omnibus proposal’s published outline does not include any improvements to the GDPR.

This omission represents a critical missed opportunity. While the GDPR’s substantive provisions aren’t necessarily the core problem—as the regulation was intended to protect personal data while acknowledging the need to balance privacy with other fundamental rights and societal goals—the law’s enforcement structure has produced a disproportionate, absolutist interpretation of privacy law. The real challenge facing European businesses is not merely this administrative burden but fundamental uncertainty about compliance boundaries, driven by an enforcement framework that systematically privileges privacy over all other objectives of EU law.

The current regime empowers DPAs as both prosecutor and judge, wielding enormous power to impose crippling fines in service of a privacy-maximalist agenda. DPAs appear driven by the belief that their sole responsibility is to maximize privacy and data protection, requiring regulated businesses to demonstrate—against an extremely high standard of proof—that any other interests might justify deviating from the most privacy-focused approach. While regulators acknowledge GDPR’s Recital 4, which explicitly addresses proportionality and the non-absolute nature of privacy rights, this principle remains subordinated to enforcement practices that treat privacy as supreme.

The recent EDPB Opinion on AI models exemplifies this structural failure: It provides a lengthy list of compliance measures, while offering no guarantees that following such measures will satisfy enforcement authorities. It therefore effectively grants regulators near-limitless discretion, while providing minimal practical guidance to those trying to innovate responsibly.[4]

This fundamental disconnect from economic realities means EU businesses cannot rely on any consistent interpretation of compliance—even those ostensibly tested in enforcement proceedings. Even the threat of discretionary regulatory enforcement, combined with the risk of heavy fines, can chill investment decisions significantly, as well as innovation at the margins.

The approach adopted by CNIL, the French DPA, in its guidance on AI and the GDPR contrasts favourably with the EDPB document.[5] While CNIL demonstrated that proportionate and pragmatic guidance is possible under the GDPR is possible, it is clear that the EDPB is currently institutionally incapable of following CNIL’s lead.

The enforcement framework’s institutional bias toward privacy absolutism contradicts not only the GDPR’s text but also the EU’s broader ambitions, as outlined in the Draghi report and the Commission’s stated goals. This model fails to adequately represent the non-privacy rights and interests of individuals—particularly vital interests like economic security that fall within the purview of political authorities whose involvement is currently seen as anathema under the interpretation of DPA “independence”.

The Commission’s proposed GDPR Procedural Regulation fails to address these fundamental issues, merely tinkering at the margins while leaving the privacy-absolutist enforcement structure intact. Rather than focusing on recordkeeping requirements for SMEs—a performative exercise that would waste this opportunity—Europe needs a proportionate data-protection framework that avoids absolutist zealotry and recognizes privacy as one vital interest among many, including economic security and freedom of expression.

Without credible guarantees that the GDPR will be interpreted through the lens of proportionality and in harmony with the full spectrum of EU law objectives—from the Digital Single Market to fundamental freedoms—any simplification efforts will remain superficial. The Commission should recognize that meaningful GDPR simplification requires addressing this structural imbalance in enforcement.

How can this be addressed?

First, the main text of the GDPR could be amended with explicit references to the principle of proportionality, the risk-based approach, and the need to balance privacy and data protection with other rights and values (e.g., amending and moving the content of Recital 4). This would constitute an important declaration but would likely be insufficient, given the DPAs’ entrenched attitudes.

Second, the principle of proportionality could be embedded institutionally, ensuring that data protection serves its intended purpose without undermining Europe’s economic competitiveness and other fundamental values. One way to move in this direction would be to involve an independent, multidisciplinary tribunal to decide on enforcement actions and guidance documents—a body not stacked with privacy lawyers but that would include economists, business experts, and generalist judges who could weigh privacy alongside other fundamental rights and Europe’s need for innovation and growth.[6] Such a tribunal’s legal framework could require it to articulate how each decision balances data protection against other fundamental rights and economic realities, ensuring that privacy isn’t automatically placed above freedoms such as conducting business, research, or expression.

IV. How to Identify Simplification Goals: Significant Indirect Effects

Given our mission to apply law & economics analysis, we also wish to comment on the methodology for identifying simplification priorities. We will do so in this section using the example of the importance of taking impacts on business users seriously in policy choices. By focusing on removing some administrative barriers directly imposed on some businesses, the Commission may lose sight of more serious barriers created by imposing restrictions on suppliers (e.g., online marketplaces, platforms) upon which EU SMEs and mid-caps rely. This example demonstrates that the current process of impact assessment and policy design risks failing to notice some of the very significant barriers to innovation and economic growth posed by EU law.

In the already-cited communication on “A Simpler and Faster Europe”, the Commission highlighted that “improving how we make rules” will be a priority, and that this will include “reinforced SME and competitiveness checks”.[7]

In that spirit, we stress that legal restrictions on digital-business activities are likely to constitute more significant barriers for EU businesses than mere “red tape” obligations. Moreover, such significant barriers can arise from legal duties imposed on other businesses. Impact assessments of the kind currently conducted by the Commission can easily overlook this reality.

To illustrate, consider how EU businesses and other organisations that rely on large online platforms to reach their audiences are under risk from legal restrictions imposed on those platforms.

EU data-protection authorities have demonstrated growing hostility to personalised advertising, refusing to recognise the economic nature of the relationship among online platforms, their users, and business users (advertisers).

This regulatory hostility has tended to lack serious reflection on how restrictions on ad targeting will affect business users. Many EU businesses—particularly SMEs—simply could not function without cost-effective ways to target relatively niche audiences. A niche artisanal producer or a startup launching an innovative product will often depend on the ability to reach specific audiences without the massive budgets required for broad brand advertising.

In its DMA-enforcement decision against Meta, the Commission acknowledged that Meta’s advertising platform provides unparalleled scale and personalisation capabilities. Yet the Commission’s approach would be to degrade these tools without any analysis of the collateral damage to Meta’s business users. This is an example of enforcement practice that dangerously disregards the consequences for EU businesses other than the direct addressee of the decision.

Ironically, this kind of regulatory assault on personalised advertising may prevent the emergence of the very EU digital champions that policymakers claim to want. Consider that TikTok—one of the biggest challengers to established online platforms in recent years—was to a considerable extent promoted through effective advertising on existing platforms like Facebook and Instagram. If we hope for future EU challengers to emerge and scale, closing off the most effective ways to reach EU audiences will be profoundly counterproductive.

New entrants and challengers depend on targeted advertising both to acquire users cost-effectively and to generate revenue. By making personalised advertising increasingly difficult or impossible, EU regulations risk creating a moat around incumbent positions—the opposite of the stated goal of promoting contestability.

Analogous downstream consequences of regulations that target platforms are already visible in the political-advertising sphere. Google, Meta, and Microsoft have turned off political advertising in the EU rather than risk falling afoul of unclear rules around political ads.[8] As reported in the press, this has significant implications for political and issue messaging in the EU, limiting the ability of political parties, civil-society organisations, and advocacy groups to reach citizens effectively. This shutdown should serve as a cautionary tale. If personalised advertising is significantly restricted for standard commercial ads, the impact on EU businesses would be far more disruptive.

Another example of the consequences of ignoring business-user impacts is the DMA’s demonstrated effect on hotels. When the DMA was enforced against Google’s hotel-search features, European hotels experienced a 30% drop in direct booking traffic and a 36% decline in direct bookings.[9]

Moreover, among the primary beneficiaries were large American online travel agencies like Booking.com and Expedia, which captured the market share that EU hotels lost. HOTREC, representing more than two million European hospitality businesses, described this outcome as “paradoxical”: an EU law intended to promote competition that ended up harming EU small businesses, while benefiting large U.S. corporations.[10]

The lesson from this example is that the EU digital acquis—including the GDPR, but also asymmetric regulations like the DMA and the DSA—need to be subjected to careful analysis of their negative indirect effects. The impact assessment behind the DMA can serve as a case study of poor analysis of indirect effects, where positive indirect effects were assumed without robust analysis, while negative indirect effects were ignored.

[1] European Data Protection Board, Guidelines 2/2023 on Technical Scope of Article 5(3) of the ePrivacy Directive (7 October 2024), https://www.edpb.europa.eu/our-work-tools/our-documents/guidelines/guidelines-22023-technical-scope-art-53-eprivacy-directive_en.

[2] Dir Auer & Lazar Radic, A Europe Fit for the Age of Startups: Rhetoric and Reality in the EU’s Digital Package, Int’l Ctr. L & Econ. (August 2025), https://laweconcenter.org/resources/a-europe-fit-for-the-age-of-startups-rhetoric-and-reality-in-the-eus-digital-package.

[3] European Commission, A Simpler and Faster Europe: Communication on Implementation and Simplification (1 February 2025), available at https://commission.europa.eu/document/download/8556fc33-48a3-4a96-94e8-8ecacef1ea18_en?filename=250201_Simplification_Communication_en.pdf.

[4] European Data Protection Board, Opinion 28/2024 on Certain Data Protection Aspects (Art. 64) (2024), https://www.edpb.europa.eu/our-work-tools/our-documents/opinion-board-art-64/opinion-282024-certain-data-protection-aspects_en.

[5] Commission Nationale de l’Informatique et des Libertés (CNIL), IA et RGPD : la CNIL Publie ses Nouvelles Recommandations Pour Accompagner une Innovation Responsable (7 February 2025), available at https://www.cnil.fr/fr/ia-et-rgpd-la-cnil-publie-ses-nouvelles-recommandations-pour-accompagner-une-innovation-responsable.

[6] See Mikołaj Barczentewicz, A Serious Target for Improving EU Regulation: GDPR Enforcement, EUTechReg (27 February 2025) https://eutechreg.com/p/a-serious-target-for-improving-eu.

[7] European Commission, supra note 3.

[8] Ellen O’Regan & Eliza Gkritsi, EU Political-Ad Rules Kick In for Google, Meta, Microsoft, Politico (May 2025), https://www.politico.eu/article/eu-political-ad-rules-google-meta-microsoft-big-tech-kick-in.

[9] Javier Delgado, DMA Implementation Sinks 30% of Clicks and Bookings on Google Hotel Ads, Mirai Blog (7 May 2024), https://www.mirai.com/blog/dma-implementation-sinks-30-of-clicks-and-bookings-on-google-hotel-ads.

[10] HOTREC, Joint Industry Statement on Google Search and Article 6.5 of the Digital Markets Act (6 March 2024), https://www.hotrec.eu/en/policies/joint_industry_statement_on_google_search_and_article_6-5_of_the_digital_markets_act.html.

Regulatory Comments

ICLE Comments to UK IPO on Standard-Essential Patents

Executive Summary We are pleased to offer comments to the Intellectual Property Office (IPO) regarding its consultation on standard-essential patents (SEPs).[1] The International Center for . . .

Executive Summary

We are pleased to offer comments to the Intellectual Property Office (IPO) regarding its consultation on standard-essential patents (SEPs).[1] The International Center for Law & Economics (ICLE) is a nonprofit, nonpartisan research organization whose core mission is to promote the application of law & economics methodologies to inform public-policy discussion. Our work focuses on developing intellectually rigorous, data-driven analyses to foster efficient policy solutions that enhance consumer welfare and global economic growth.

The IPO is considering new regulations for SEPs—patents necessary to implement technical standards, such as those used in smartphones. The IPO claims “systemic issues” require government intervention, but this assertion contradicts substantial evidence and repeats mistakes recently made by the European Union.

The IPO’s premise of market failure lacks empirical support. A comprehensive 2023 European Commission study found no evidence that current SEP-licensing practices deter innovation or cause companies to avoid standardized technologies. SEP litigation rates are low and falling relative to other patent disputes. The European Commission recently withdrew its own similar regulation after it failed to gain support, largely because it could not demonstrate a problem requiring intervention.

The consultation focuses exclusively on “patent holdup”—the theoretical risk that patent owners might overcharge implementers. It ignores, however, the well-documented problem of “patent holdout”, where companies deliberately delay or refuse licensing, forcing patent owners into costly litigation. A 2024 study estimated patent owners lost $7-28 billion in 2021 alone due to holdout behaviour. Proceeding with interventions shaped by this one-sided perspective is likely to foster proposals that systematically favour infringers over innovators.

There are serious problems with each of the main interventions the IPO has thus far proposed. The so-called Rate Determination Track is a government price-setting mechanism that would function as a price-control mechanism, replacing efficient market negotiations with bureaucratic decisions. It would encourage companies to avoid good-faith negotiations and would ultimately diminish the incentives to innovate. A second potential intervention would establish mandatory databases and essentiality checks, which impose costly burdens on innovators while providing questionable value. Given that only an estimated 25-40% of declared SEPs are truly essential, creating databases with poor signal-to-noise ratios could enable strategic delay tactics. Finally, weakening inventors’ ability to obtain injunctions would do more harm than good. Limiting injunctions to prevent unauthorized use would remove the primary deterrent against infringement. This would, in turn, encourage “efficient infringement” strategies, where companies simply use technology without permission and treat eventual royalties as business costs.

These proposals would reduce patents’ value and enforceability, directly contradicting the IPO’s mission to promote innovation and economic growth. They would particularly harm small companies and startups that rely on strong patents to attract investment. By weakening patent protection, the UK would inadvertently subsidize foreign manufacturers, while undermining its own innovators.

The UK already possesses excellent courts capable of resolving these disputes. Rather than create new regulations to more stringently police a non-existent problem, the IPO should maintain strong property rights and allow market-based solutions to develop naturally.

I. Introduction and Overview

The IPO’s consultation proceeds from the assertion that “available evidence indicates there are systemic issues in the SEPs ecosystem around transparency and dispute resolution that may require government intervention”.[2] This premise, which suggests a dysfunctional market in need of correction, animates the series of regulatory proposals that follow.

This narrative, however, is not new. It closely mirrors the one that underpinned the European Commission’s proposed SEP regulation, an initiative that was ultimately withdrawn.[3] As the Research Network for Digital Ecosystem, Economic Policy, and Innovation (Deep-In) observed in its comments to this consultation, the concerns about systemic inefficiencies “lack robust support from empirical evidence”.[4] The central criticism levelled against the EU initiative was its weak economic justification, as there was “no discernible evidence of a market failure that needs to be addressed”.[5]

The empirical record directly contradicts the premise of a systemic market failure. A comprehensive 2023 study commissioned by the European Commission and authored by Justus Baron, Pere Arque-Castells, and others examined the SEP-licensing landscape in detail.[6] The study concluded that existing empirical evidence on the causal effects of current SEP-licensing conditions is “largely inconclusive”.[7] Specifically, the study found no evidence that frictions in licensing under fair, reasonable, and non-discriminatory (FRAND) terms deter patent holders from contributing to standards development or cause technology implementers to choose alternative, non-standardized technologies.[8] Furthermore, the study found that the prevalence of SEP litigation is low when compared to patent litigation involving non-SEPs and that it is not increasing over time.[9] In fact, the share of declared SEPs subject to litigation has recently decreased.[10]

The IPO’s consultation proceeds as if this body of evidence does not exist, and makes only a passing reference to Baron et al.’s research published by the European Commission.[11] By adopting a narrative of market failure that has already been empirically tested and found wanting in a neighbouring jurisdiction, the IPO appears to engage in a form of regulatory cascade. This process, where a policy idea is perpetuated despite a lack of evidentiary support, suggests a policymaking process driven by theoretical concerns or stakeholder lobbying, rather than robust, independent data.

Given this fundamental disconnect between the consultation’s premise and the available evidence, the IPO’s proposed interventions are solutions in search of a problem. This analysis will demonstrate that the IPO’s diagnosis of “systemic issues” is not supported by the data, and that the proposed remedies are therefore unwarranted and likely to cause significant unintended economic harm.

II. Lessons from the EU’s Failed SEP Regulation

In April 2023, the European Commission unveiled a sweeping proposal to regulate SEPs. The regulation aimed to increase transparency and efficiency by creating a new centralized bureaucracy within the EU Intellectual Property Office (EUIPO). This new “Competence Centre” would have administered a mandatory SEP register, conducted “essentiality checks”, and most controversially, overseen a mandatory, prelitigation FRAND-determination process that would have delayed a patent holder’s right to seek redress in court.

ICLE explained at the time that the proposal was a solution in search of a problem.[12] The regulation was an unnecessary and dangerous intervention that lacked sound economic justification. The Commission’s own impact assessment failed to provide evidence of a systemic market failure. Instead, data showed that SEP litigation in Europe was stable or even falling.

The proposal’s core mechanism—a mandatory nine-month conciliation process before a patent holder could go to court—would have dismantled the existing judicial framework and tilted the playing field decisively in favor of implementers. By removing the immediate threat of an injunction, it would have created a “safe harbour” for infringement and exacerbated the problem of patent holdout.

The proposal triggered a fierce battle. Implementer groups—such as the Fair Standards Alliance—praised it as a necessary check on patent holdup. Major European innovators like Ericsson and Nokia, however, condemned it as an unbalanced intervention that would undermine Europe’s technological leadership and jeopardize the global standardization ecosystem.

Ultimately, the regulation failed to gain sufficient political support, and the Commission announced its withdrawal in early 2025. The demise of the EU SEP regulation is a powerful, real-world validation of the law & economics critique of prescriptive, top-down regulation. It demonstrates that, when they are based on flawed economic logic and a lack of empirical evidence, such interventions can and should be rejected by the market and political processes.

III.    The Consultation’s Pronounced Bias Against Patent Holders

The IPO consultation states its ambition to shape a “balanced ecosystem” that ensures “SEP holders can protect and enforce their rights and licensees can develop standard compliant products”.[13] Yet the document’s explicit objective is to “help implementers, especially SMEs, navigate and better understand the SEPs ecosystem”.[14] This framing reveals an analytical asymmetry that pervades the entire consultation.

The document’s focus reflects a pronounced “holdup bias” that assumes SEP holders can leverage their position to demand supra-FRAND royalties after a standard is adopted, and that implementers have made sunk investments that lock them into using the standard.[15] The IPO’s concern about licensing offers that have “exceeded court adjudicated rates by 4-500 times”[16] and the “threat of injunctions” being used to extract high rates is a clear manifestation of this bias.[17]

While focusing on this theoretical risk, the consultation entirely disregards the countervailing and empirically more significant problem of patent “holdout”, also known as “efficient infringement”.[18] Holdout occurs when technology implementers strategically delay or refuse to take a license for the patents they are using, forcing innovators into costly and protracted litigation to enforce their property rights. This is not a trivial omission. As Deep-In reports, UK courts have recognized holdup and holdout are “two sides of the same coin”, and the FRAND commitment is designed to address both forms of opportunistic behaviour simultaneously.[19]

The economic impact of patent holdout is substantial and well-documented. A 2024 study by Bowman Heiden and Justus Baron estimates that patent owners in the cellular SEP sector lost between $7 billion and $28 billion in 2021 alone due to holdout strategies.[20] This “royalty gap”—the difference between the reasonable value of a license and the royalties that patent holders are actually able to recoup—represents a large uncompensated transfer of value from the firms that invest in foundational research and development to firms that infringe their intellectual property.

The policy options presented by the IPO reflect this analytical imbalance. The proposals uniformly target SEP holders, imposing new obligations such as mandatory information disclosure and creating new constraints through a government-administered rate-setting process. Simultaneously, they offer no corresponding mechanism to ensure the timely and effective enforcement of patent holders’ rights against recalcitrant infringers. This one-sided approach creates a system of asymmetric rules that favours infringers over innovators. This regulatory framework would systematically disadvantage the party that invested in creating the technology in favour of the party using it without permission. The long-term consequences of such a policy include a reduction in the expected return on innovation, leading to less investment in the foundational technologies that drive economic growth.

IV. The Proposals’ Unintended Consequences and Economic Costs

While presented as measures to improve “efficiency” and “transparency”, the IPO’s proposals are likely to introduce significant economic distortions, increase costs, and ultimately harm the very innovation they intend to support.

A. The Rate-Determination Track: The Perils of Price Regulation

The proposal to create a Rate Determination Track (RDT) within the Intellectual Property Enterprise Court (IPEC) to provide a “binding rate determination” is, to be blunt, a price-control mechanism.[21] It substitutes the judgment of an administrative or judicial body for the market’s price-discovery function, which is best carried out through private negotiations among parties with the most complete information.

Regulators inherently lack the specific knowledge of value, risk, and commercial context that negotiating parties possess. Scholars such as Douglas H. Ginsburg, former head of the U.S. Justice Department’s (DOJ) Antitrust Division, have argued that government price setting is inefficient and interferes with free-market competition.[22] A government-set rate is highly unlikely to reflect the efficient, market-clearing price. Recognizing this danger, U.S. antitrust agencies do not regulate prices, correctly allowing firms to unilaterally set or privately negotiate them.

The existence of a low-cost RDT would also distort the incentives for both parties in a licensing negotiation. It would encourage holdout, as an implementer could refuse to negotiate in good faith, knowing it can force the matter into a subsidized administrative process with limited downside risk. It also creates incentives for parties to present extreme positions, anticipating that a decisionmaker will simply “split the difference”, a well-documented problem in damages litigation that leads to unreasonable and unpredictable outcomes.[23] The proposed publication of RDT-determined rates would further harm the market by creating artificial price anchors, chilling private negotiations, and leading to inflexible, one-size-fits-all outcomes, rather than tailored and efficient agreements.

The most damaging unintended consequence of such price regulation is its effect on innovation. By artificially suppressing the potential return on investment for successful technologies, price controls blunt the incentive to innovate in the first place.[24] This outcome directly contradicts the IPO’s stated mission “to help grow the economy by developing an IP system that encourages investment in innovation and creativity”.[25]

B. Mandatory Information Disclosure and Essentiality Services

The proposal to mandate the provision of standard-related patent information and create a searchable database imposes direct compliance costs on innovators.[26] This administrative burden functions as a tax on the very innovative activity the government seeks to foster.

The utility of such a database is highly questionable. The IPO’s own consultation document acknowledges that “only about 25-40% of all declared SEPs are truly essential to a given standard”.[27] Igor Nikolic explains that, because standards-development organizations (SDOs) prioritize comprehensiveness to avoid undeclared patents, “there are far more disclosed patents that are potentially essential than there are patents that end up truly being essential”, with empirical studies showing true essentiality rates as low as 10-40%.[28]

More importantly, Nikolic highlights that essentiality is only one piece of a complex legal puzzle. For a licensee, the critical questions also include infringement and validity. A patent may theoretically be essential to a standard but not infringed by a specific product, or it may be invalid. For example, a U.S. study found that, in litigation, SEPs were held to be infringed in only 30.7% of cases.[29] Therefore, a government service that provides only an “essentiality check” offers a false and incomplete sense of certainty. Moreover, a mandatory database would be overwhelmingly populated with nonessential patents, creating a low signal-to-noise ratio. For licensees, navigating this data to determine their actual obligations would remain a complex task, for which an unreliable database would certainly increase the complexity.

Rather than facilitating efficient licensing, such a database—along with a potential government essentiality-checking service—could become a new tool for strategic delay. Implementers could leverage the high rate of “over-declaration” to challenge entire patent portfolios and bog down negotiations, a tactic that benefits the infringer at the expense of the innovator. Furthermore, a government-run or accredited service risks crowding out existing and emerging private-sector solutions, such as commercial essentiality services and patent pools, which are more likely to be efficient and responsive to market needs.

C. Remedies and Pre-Action Protocols

The consultation’s framing of injunctions as a “threat” used to “extract ‘supra-FRAND’ licence rates” fundamentally misrepresents their economic function.[30] An injunction is not a threat—it is the legal remedy that gives effect to a property owner’s core right to exclude others from using their property without permission. It is a foundational element of the patent system.[31]

Indeed, the credible threat of an injunction is the primary mechanism that deters patent holdout. Without it, an implementer’s rational strategy is often to infringe, continue to profit from the technology, and treat any eventual royalty payment as a mere cost of doing business—a practice we note above is sometimes known as “efficient infringement”. This dynamic systematically undercompensates innovators and reduces the value of their patents. Geoffrey Manne explains:

[T]he credible threat of an injunction deters infringement in the first place. This results from the serious consequences of an injunction for an infringer, including the loss of sunk investment. [A] predictable injunction threat will promote licensing by the parties. Private contracting is generally preferable to a compulsory licensing regime because the parties will have better information about the appropriate terms of a license than would a court, and more flexibility in fashioning efficient agreements. But denying an injunction every time an infringer’s switching costs exceed the economic value of the invention would dramatically undermine the ability of a patent to deter infringement and encourage innovation. For this reason, courts should grant injunctions in the majority of cases.[32]

Weakening SEP enforcement has direct geopolitical and strategic implications. Policies that limit injunctive relief inadvertently support the industrial strategies of nations like China, which are net implementers of Western technology.[33] A policy that weakens SEP protection for UK-based innovators amounts to a subsidy for foreign manufacturers, undermining the UK’s stated goal of securing technological leadership.[34] This is particularly concerning given that the framework established by the Court of Justice of the European Union (CJEU) in Huawei v. ZTE already provides a balance, making injunctive relief unavailable against a “willing licensee”.[35] The IPO’s consultation appears to seek a further weakening of patent-holder rights beyond this established, balanced standard.

The IPO’s proposals are thus in direct conflict with its own stated goal of promoting economic growth and innovation. The IPO’s primary mission is “to enable economic growth” by encouraging “investment in innovation and creativity”.[36] Economic growth in technology sectors is driven by investment in research and development undertaken in expectation of a return secured through enforceable intellectual-property rights. The IPO’s proposals—price controls via the RDT, increased administrative burdens, and weakened injunctive relief—all serve to reduce a patent’s expected value and enforceability. By reducing the value of the primary asset that underpins technology investment, these policies will necessarily reduce the incentive to invest in R&D in the UK.

This is particularly harmful to the SMEs and startups the IPO claims to help, as these entities rely on strong patents to attract venture capital and defend themselves against infringement by larger established firms. Therefore, the IPO’s policy initiative is internally incoherent, proposing measures that will actively undermine its foundational mission.

V. Conclusion

The proposals outlined in the IPO’s consultation are based on a flawed premise not supported by the available empirical evidence. Rather than correcting “systemic issues”, they are likely to create new ones—distorting markets, increasing costs for innovators, and chilling the investment that drives the UK’s technology sector. A more constructive path forward would be based on a clear-eyed assessment of the evidence and a renewed commitment to the principles of property rights and private ordering.

The fundamental premise of the consultation—that the SEP ecosystem suffers from a market failure that requires government intervention—should be rejected. The IPO should withdraw the proposals, which are solutions to a problem that the evidence shows does not exist in any systemic way.

Instead of weakening patent rights, UK policy should focus on reinforcing them. This would mean preserving the availability of injunctive relief as the primary remedy against infringement, consistent with the balanced approach in existing jurisprudence. A strong property-rights regime is the most effective way to combat the real and costly problem of patent holdout.

Complex commercial disputes over FRAND licensing are best resolved through private negotiation between sophisticated parties, backstopped by the existing court system. Contract law—not administrative regulation or antitrust—is the proper domain for these issues.[37] The UK’s own judicial system has proven exceptionally capable in this regard. For example, the landmark decision in InterDigital v. Lenovo demonstrates a sophisticated, economically grounded framework that relies on market-based evidence and directly confronts the problem of patent holdout.[38] The UK already possesses a world-class, market-respecting judicial path to resolve these disputes, making the IPO’s proposed top-down regulatory path both unnecessary and inferior.

Finally, the government should allow market-led solutions to evolve. The consultation itself notes the emergence of patent pools in mature markets. These voluntary, private-sector arrangements are far more efficient and adaptable than top-down government regulation. The government should foster an environment where these solutions can develop, not crowd them out with unnecessary and harmful interventions. A policy of regulatory restraint is the best way to support a dynamic and innovative technology sector in the UK.

[1] Standard Essential Patents Consultation – CP 1357, Intell. Prop. Off. (July 2025), available at https://assets.publishing.service.gov.uk/media/6874dea293d52d8659e4653b/Standard_Essential_Patents_Consultation__Print-ready_PDF_.pdf [hereafter “Consultation”].

[2] Consultation, ¶ 2.

[3] Proposal for a Regulation of the European Parliament and of the Council on Standard Essential Patents and Amending Regulation (EU) 2017/1001, Eur. Comm’n, COM(2023)232; see also Commission Work Programme 2025—Moving Forward Together: A Bolder, Simpler, Faster Union, Eur. Comm’n, COM(2025) 45 final, Annex IV, No. 17.

[4] Giuseppe Colangelo & Antonio Manganelli, Deep-In Comments (2025), at 1 [hereafter “Deep-In”]

[5] Id.

[6] Justus Baron, Pere Arque-Castells, Amandine Leonard, Tim Pohlmann, & Eric Sergheraert, Empirical Assessment of Potential Challenges in SEP Licensing, Study for the European Commission (2023), available at https://www.lexisnexisip.com/wp-content/uploads/2023/09/Empirical-Assessment-of-Potential-Challenges-in-SEP-Licensing.pdf.

[7] Id. at 185.

[8] Id. at 175, 179.

[9] Id. at 108-11.

[10] Id.

[11] Consultation, Annex 2, Supporting evidence.

[12] Geoffrey A. Manne, Dirk Auer, Kristian Stout, & Ben Sperry, Comments of the International Center for Law & Economics in Response to EU Commission Call for Evidence Concerning a New Framework for Standard-Essential Patents, Int’l Ctr. for L. & Econ. (8 May 2022), available at https://laweconcenter.org/wp-content/uploads/2022/05/ICLE-Response-to-EU-Commission-Call-for-Evidence-on-SEPs.pdf; Giuseppe Colangelo & Geoffrey A. Manne, If Necessity Is the Mother of Invention, New EU SEP Rules Are Decidedly Unnecessary, Truth on the Mkt. (12 April 2023), https://truthonthemarket.com/2023/04/25/if-necessity-is-the-mother-of-invention-new-eu-sep-rules-are-decidedly-unnecessary.

[13] Consultation ¶ 48.

[14] Id. ¶ 46.

[15] Id. ¶ 73 (“Licensees hold less information than licensors on which patents are truly essential, which makes it difficult for licensees to determine with confidence if a license is required. This in turn can lengthen licensing negotiations and potentially lead to payment of supra-FRAND license terms, or even court litigation”.), see also ¶¶ 43, 53, 59.

[16] Id. ¶ 36.

[17] Id. ¶ 59.

[18] Richard A. Epstein & Kayvan B. Noroozi, Why Incentives for “Patent Holdout” Threaten to Dismantle FRAND, and Why It Matters, 32 Berkeley Tech. L.J. (2017) 1381, 1384 (“We use the terms ‘patent holdup’ and ‘patent holdout’ as they have been used in the extensive patent literature, and in the general economics literature on holdup and holdout problems. In general, by ‘patent holdup’ we mean the theoretical claim that innovators of standard-essential patents attempt to extract excessively large royalties from implementers after those implementers have committed to a particular technological standard that requires the use of the patent(s) in question—that is, a standard that renders the patent(s) ‘essential.’ Under the ‘patent holdup’ theory, the royalties in question are excessively large because they exceed the ‘true’ value of the invention(s) in question, and are derived, so the theory goes, because the innovator can leverage the implementer’s sunk cost in committing to the standard to extract more than a fair royalty. By ‘patent holdout’ we mean the converse problem—that an implementer refuses to negotiate in good faith with an innovator for a license to valid patent(s) that the implementer infringes, and instead forces the innovator to either undertake significant litigation costs and time delays to extract a licensing payment through a court order, or else to simply drop the matter because the licensing game is no longer worth the candle. We also use the term ‘efficient infringement’ synonymously with ‘patent holdout’ here”.)

[19] Deep-In at 3.

[20] Bowman Heiden & Justus Baron, The Economic Impact of Patent Holdout, 38 Harv. J. L. Tech. 637, 668 (2024).

[21] Consultation, ¶¶ 61-71.

[22] See, e.g., Douglas H. Ginsburg, Bruce H. Kobayashi, Koren W. Wong-Ervin, & Joshua D. Wright, “Excessive Royalty” Prohibitions and the Dangers of Punishing Vigorous Competition and Harming Incentives to Innovate, CPI Antitrust Chron. (March 2016), available at https://www.competitionpolicyinternational.com/wp-content/uploads/2016/03/Excessive-Royalty-Prohibitions.pdf.

[23] Dan McManus, Incentives Must Change: Addressing the Unpredictability of Reasonable Royalty Damages, 5 Am. Univ. Intell. Prop. Brief 1 (2013), (“If a litigating party knows that the decision-maker is simply going to split the difference, then that party has the incentive to argue for damages as far away from their opposing party as possible. This tactic allows the party to skew the midpoint of the resulting split to their side as much as possible. This misaligned incentive is the root cause of the unpredictability in reasonable royalty damages and other proposals have failed to address it”.)

[24] Ginsburg et al., supra note 22.

[25] Consultation ¶ 21.

[26] Consultation ¶¶ 72-81, 87-88.

[27] Consultation ¶ 38.

[28] Igor Nikolic, European Commission’s Leaked SEP Regulation Would Increase Costs for Innovators, Hurt EU Competitiveness, and Fail to Reduce Litigation, Truth on the Mkt. (7 April 2023), https://truthonthemarket.com/2023/04/07/european-commissions-leaked-sep-regulation-would-increase-costs-for-innovators-hurt-eu-competitiveness-and-fail-to-reduce-litigation.

[29] Mark A. Lemley & Timothy Simcoe, How Essential Are Essential Patents? 104 Cornell L. Rev. 607 (2019) (“SEPs are no more likely to be found infringed than non-SEPs. Of the 215 infringement decisions in our study, 127 involved SEPs and 88 did not. The SEP infringement win rate was 30.7%, not appreciably (or statistically) different than the non-SEP infringement win rate of 29.5%”.)

[30] Consultation ¶ 59.

[31] See, e.g., Smith International, Inc. v. Hughes Tool Co. 718 F.2d 1573, 1577–78 (Fed. Cir. 1983) (“Without this injunctive power of the courts, the right to exclude granted by the patent would be diminished, and the express purpose of the Constitution and Congress, to promote the progress of the useful arts, would be seriously undermined. The patent owner would lack much of the ‘leverage,’ afforded by the right to exclude, to enjoy the full value of his invention in the market place. Without the right to obtain an injunction, the right to exclude granted to the patentee would have only a fraction of the value it was intended to have, and would no longer be as great an incentive to engage in the toils of scientific and technological research”.); see also Geoffrey A. Manne, Kristian Stout, Julian Morris, & Dirk Auer, The Deterioration of Appropriate Remedies in Patent Disputes, 21 Federalist Soc. Rev. 158, 161 (2020) (“[Patent] laws would be meaningless, however, without the ability to enforce them and remedy breaches. And one of the most important remedies is the injunction”.).

[32] Geoffrey A. Manne, The Final Order in the FTC’s Google Standard-Essential Patents Case and the Continuing Danger to Standard-Setting, Truth on the Mkt. (31 July 2013), https://truthonthemarket.com/2013/07/31/the-final-order-in-the-ftcs-google-standard-essential-patents-case-and-the-continuing-danger-to-standard-setting.

[33] Geoffrey A. Manne, Unpacking the Flawed 2021 Draft USPTO, NIST, & DOJ Policy Statement on Standard-Essential Patents (SEPs), Truth on the Mkt. (8 February 2022), https://truthonthemarket.com/2022/02/08/unpacking-the-flawed-2021-draft-uspto-nist-doj-policy-statement-on-standard-essential-patents-seps.

[34] Department for Science, Innovation & Technology and Foreign, Commonwealth & Development Office, The UK’s International Technology Strategy, CP 810 (March 2023), https://www.gov.uk/government/publications/uk-international-technology-strategy/the-uks-international-technology-strategy.

[35] Giuseppe Colangelo, FRAND Determinations Under the EU SEP Proposal: Discarding the Huawei Framework, Int’l Ctr. for L. & Econ. (15 November 2023), available at https://laweconcenter.org/wp-content/uploads/2023/11/SEP-wp-28.9.pdf.

[36] Consultation, ¶ 20-21.

[37] Ginsburg et al., supra note 22; see also, Alden Abbott, A Comprehensive Overview (and Sound Analysis) of the Law and Economics of FRAND Litigation, Here and Abroad, Truth on the Mkt. (15 June 2017), https://truthonthemarket.com/2017/06/15/a-comprehensive-overview-and-sound-analysis-of-the-law-and-economics-of-frand-litigation-here-and-abroad.

[38] See Valéria Silva, FRAND-Licensing Litigation Across the Atlantic: A Comparative Assessment of US and UK Jurisprudence on Telecom Disputes, Int’l Ctr. for L. & Econ. (8 April 2025) (“Similarly, in InterDigital v. Lenovo, where InterDigital sued Lenovo for patent infringement in the UK, the UK court further cemented its position as a forum for global FRAND determinations. Justice James Mellor set a global FRAND rate for InterDigital’s 3G, 4G, and 5G SEP portfolio and the court rejected Lenovo’s arguments for country-by-country licensing. These cases illustrate the UK courts’ consistent willingness to set global FRAND terms in such situations, their evolving methodologies to determine rates, and how they seek to balance the interests of SEP holders and implementers—further solidifying the principles established in Unwired Planet”.)

Regulatory Comments