Antitrust Implications of the Build vs. Buy Playbook in the AI Era
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Arpita Patnaik, Yajing Jiang, and Ishuwar Seetharam argue that antitrust scrutiny of artificial intelligence (AI) acquisitions and partnerships should focus on why firms choose to build, buy, or partner, rather than assume that a deal displaces in-house development or future competition. Building AI internally offers customization and control over intellectual property and proprietary data but requires substantial investment in computing resources, talent, and time. Buying or partnering can lower those barriers and accelerate innovation and market entry. These arrangements still carry risks, including eliminating independent innovators, restricting competitors’ access to essential inputs, and creating vendor lock-in. The authors advocate case-by-case assessments that weigh those risks against efficiencies, supported by measures such as interoperability and nonexclusive partnerships.
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