The Case for Vigilance in AI Markets

By: Stacey Dogan (ProMarket)

Antitrust authorities in the U.S. and globally are increasingly focused on the expanding network of relationships between dominant tech companies and artificial intelligence (AI) developers. These partnerships, formed rapidly and often involving significant financial investments, come in various transactional forms. Tech firms portray these deals as fostering innovation and enhancing efficiency, claiming that the AI market remains highly competitive.

However, regulators are skeptical. While no formal challenges have yet been made, competition authorities in the U.S., European Union, United Kingdom, and other regions have adopted a stance of active scrutiny. Through information requests, investigations, policy statements, and public commentary, regulators have made it clear that they will closely monitor these developments. Their aim is to evaluate each deal in real time, ensuring they can respond swiftly to transactions that may lead to anticompetitive outcomes.

This strategy of vigilant oversight represents a pragmatic attempt to preserve the disruptive potential of AI technologies and maintain competitive markets. It also reflects a determination to avoid the mistakes made in past waves of tech disruption, such as those in personal computing, search engines, and social media, where a “wait-and-see” approach allowed certain firms to dominate.

Disruptive technologies like AI have the power to reshape markets, challenge established leaders, and fuel innovation. Economist Joseph Schumpeter described this process as “creative destruction,” in which new entrants challenge incumbents, leading to technological progress and, eventually, lower prices and better products for consumers. Disruption can also decentralize power, helping to prevent entrenched firms from gaining too much control over the economy, politics, and society.

Yet, even without the recent wave of deals, the nature of AI itself makes such disruption challenging, particularly in the realm of foundation models, which require immense computational power and vast datasets to develop. The barriers to entry are high, and market participation demands access to specialized resources—such as advanced chips, computing infrastructure, data, talent, and capital—many of which are controlled by Big Tech giants like Google and Amazon. These same companies also control the platforms, like search engines and social media networks, that are essential for delivering AI applications to consumers…

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