Don’t Freeze the AI Race at the Starting Line
Regulators keep warning that AI markets are about to be captured by Big Tech. The awkward fact is that AI markets keep refusing to cooperate. Several years into the generative-AI boom, the sector still looks less like a coronation than a street fight: OpenAI, Google, Meta, Amazon, Anthropic, Perplexity, Mistral, xAI, and others are battling across models, applications, distribution, infrastructure, and enterprise services.
As I argued recently, “durable market power and demonstrable competitive harm remain elusive.” The market has not simply “tipped” toward Google, Meta, Amazon, Apple, or Microsoft. If anything, the most visible consumer-AI leader is OpenAI, which is reportedly preparing for an initial public offering.
Anthropic appears to have an edge in enterprise AI services, while Google and Microsoft benefit from distribution and infrastructure tied to their legacy businesses. Those advantages make them serious contenders, but hardly inevitable winners. On closer inspection, the AI ecosystem looks less like a market already captured by “Big Tech” than one defined by entry, rivalry, experimentation, and rapid technological change.
Despite those developments, a more pessimistic narrative continues to push for aggressive antitrust enforcement—and even direct state intervention—to “shape” AI markets. Advocates warn that AI could otherwise “supercharge ‘digital feudalism.’” That framing now runs through much of contemporary AI policy. The goal is no longer merely to police markets after anticompetitive conduct occurs, but to intervene ex ante—before the fact—to prevent a feared future of “private control” and “rent extraction.”
In his 2024 paper “The Case Against Preemptive Antitrust in the Generative Artificial Intelligence Ecosystem,” Jonathan Barnett argues that this turn toward enforcement in AI markets reflects a broader “preemptive approach” to antitrust. Under that approach, regulators presume certain practices by large technology firms are anticompetitive and place the burden on those firms to prove otherwise. Barnett’s warning is straightforward: in emerging markets, premature intervention risks suppressing “innocuous or efficient business practices” before regulators have enough evidence to assess their competitive effects.
That concern is especially acute in early-stage markets, where uncertainty is high and business practices that initially appear exclusionary may turn out to be competitively neutral—or affirmatively procompetitive. In AI markets, that includes product integration, minority investments, partnerships, licensing arrangements, and cloud-computing agreements that help firms assemble the complementary assets needed to compete.
Together with Dirk Auer, I have similarly warned that:
… overenforcement in the field of generative AI could engender the very harms that policymakers currently seek to avert. Indeed, preventing so-called “big tech” firms from competing in these markets (for example, by threatening competition intervention as soon as they build strategic relationships with AI startups) may thwart an important source of competition needed to keep today’s leading generative-AI firms in check.
This post examines three recent examples—from the European Union, Italy, and Brazil—that illustrate the common logic of this preemptive approach and suggest the warning is becoming increasingly urgent.