As artificial intelligence systems become increasingly expensive and resource dependant to develop, a question arises: Are we witnessing the emergence of AI as a natural monopoly? In this conversation, Berkeley Law Professor Tejas Narechania explores how the market forces driving AI consolidation create both efficiency and significant legal risks.

Professor Narechania explains the structural conditions under which a natural monopoly can form—where the high costs of developing foundational AI models and the competitive advantages of massive datasets create significant barriers to entry. He discusses how antitrust principles, network effects, and accountability risks must be considered when regulating AI market power.

Throughout the discussion, Professor Narechania draws on historical parallels in telecommunications law and explores potential legal tools, including interoperability requirements, national security concerns, and public infrastructure models to improve outcomes without stifling innovation.

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Approved for 1.0 hour of General California MCLE credit.