Antitrust & AI supply chains
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Maurice E. Stucke
Abstract
Will AI technology disrupt the current Big Tech Barons, foster competition, and ensure future disruptive innovation that improves our wellbeing? Or might the technology help a few ecosystems become even more powerful? To explore this issue, our Article outlines the current digital market dynamics that lead to winner-take-most-or-all ecosystems. After examining the emerging AI foundation model supply chain, we consider several potential antitrust risks that may arise should specific layers become concentrated and firms extend their power across layers. After raising several countervailing factors that might lessen or prevent these antitrust risks, we conclude with suggestions for the policy agenda to promote both healthy competition and innovation in the AI supply chain.
© 2025 by Theoretical Inquiries in Law
Articles in the same Issue
- Frontmatter
- AI, Competition & Markets
- Introduction
- Brave new world? Human welfare and paternalistic AI
- Regulatory insights from governmental uses of AI
- Data is infrastructure
- Synthetic futures and competition law
- The challenges of third-party pricing algorithms for competition law
- Antitrust & AI supply chains
- A general framework for analyzing the effects of algorithms on optimal competition laws
- Paywalling humans
- AI regulation: Competition, arbitrage and regulatory capture
- Tying in the age of algorithms
- User-based algorithmic auditing
Articles in the same Issue
- Frontmatter
- AI, Competition & Markets
- Introduction
- Brave new world? Human welfare and paternalistic AI
- Regulatory insights from governmental uses of AI
- Data is infrastructure
- Synthetic futures and competition law
- The challenges of third-party pricing algorithms for competition law
- Antitrust & AI supply chains
- A general framework for analyzing the effects of algorithms on optimal competition laws
- Paywalling humans
- AI regulation: Competition, arbitrage and regulatory capture
- Tying in the age of algorithms
- User-based algorithmic auditing