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Strategic Outsourcing to Shared AI Platforms

Author

Listed:
  • Byung-Cheol Kim

    (Culverhouse College of Business, University of Alabama, Tuscaloosa, AL, USA)

  • Keeyoung Rhee

    (Department of Economics, Sungkyunkwan University, Seoul, Korea)

Abstract

Firms increasingly outsource innovation to AI platforms serving their competitors, allowing one client's problem solving to improve what the platform delivers to another. We study a duopoly in which firms choose between in-house innovation and a shared AI platform. Cross-client learning occurs when both firms use the platform. Stronger learning can initially support joint use, yet eventually destabilize it as each firm's problem solving increasingly benefits its rival. Too many or too few firms may adopt the platform relative to a coordinated benchmark that maximizes their combined payoff subject to symmetric effort. Blocking cross-client learning can reduce competitive harm yet leave the firms collectively worse off.

Suggested Citation

  • Byung-Cheol Kim & Keeyoung Rhee, 2026. "Strategic Outsourcing to Shared AI Platforms," Working Papers 26-01, NET Institute.
    • Handle: RePEc:net:wpaper:2601
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    File URL: http://www.netinst.org/Kim_26-01.pdf
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    More about this item

    Keywords

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    JEL classification:

    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • L22 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Organization and Market Structure
    • L24 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Contracting Out; Joint Ventures
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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