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Title page 1

Contents 3

Executive Summary 2

Introduction 4

Competition, Innovation, and AI 6

Promoting Competitive AI Innovation 8

Competitive Markets and National Security 10

Understanding the AI Market 13

The AI Supply Chain 13

Nothing Gold Can Stay: OpenAI and the Economics of AI Development 17

AI Market Powers 21

Chokepoint 1: Computing Resources 22

Chokepoint 2: Data Access 24

Chokepoint 3: Model Access 25

Chokepoint 4: Product Distribution 26

Key Takeaways 28

Policy Goals for Promoting Competitive AI Innovation 30

Policy Goal 1: Increase Competition Among Compute Providers 30

Policy Goal 2: Level the Playing Field in the Production of AI Models and Applications 32

Policy Goal 3: Maintain Open Distribution Platforms 33

Trends to Follow 34

Conclusion 36

Authors 37

Acknowledgments 37

Endnotes 38

Figures 14

Figure 1. The AI Supply Chain 14

초록보기

In the years ahead, increasingly advanced artificial intelligence systems are expected to reshape the global economic and national security landscape. Maintaining long-term U.S. leadership in AI will require policymakers to foster a diversified, contestable, and competitive market for commercial AI systems. Competitive markets are a key driver of innovation, incentivizing incumbent firms to continuously improve their offerings and encouraging startups to bring disruptive products to the market. In addition to galvanizing innovation, promoting competition among AI developers would prevent the U.S. AI industry from becoming a digital monoculture and make the country more resilient against economic disruptions, technological surprises, and other national security risks.

As it stands today, however, the commercial AI industry seems poised to become less competitive over time. The organization of the AI supply chain, the economics of AI development, and the industry’s prevailing “bigger-is-better” paradigm give incumbent technology companies a clear advantage in the production of AI systems. These firms have both the means and motivation to use their market power to stifle competition in the AI sector. By leveraging their control over computing infrastructure, training data, foundation models, and product distribution channels, incumbents can effectively pick winners and losers in the AI market, potentially preventing disruptive upstarts and their inventions from reaching the market. If left unchecked, this behavior could undermine the long-term innovation capacity and resiliency of the U.S. AI ecosystem.

Though the commercial AI sector is still relatively young, the organization of the market is beginning to solidify. As such, it is appropriate for policymakers to begin pursuing targeted measures to foster competition within the AI ecosystem. Waiting too long to take action risks entrenching current competitive dynamics, allowing large technology incumbents to further extend their market power across the AI industry and potentially stifle domestic innovation. Such inaction could leave the United States at a long-term disadvantage against competitors like China, who have a strong incentive to pursue disruptive innovations that counteract U.S. export controls and other efforts to limit their AI capabilities.

This report proposes three broad goals that near-term policy action could target to promote lasting competition and innovation in the AI market, along with specific policy levers for government leaders to consider. These goals include: 1) Increasing competition among compute providers; 2) Leveling the playing field in the production of AI models and applications; and 3) Promoting open distribution channels for AI products.

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