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Artificial intelligence adoption and system‐wide change

Author

Listed:
  • Ajay Agrawal
  • Joshua S. Gans
  • Avi Goldfarb

Abstract

Analyses of artificial intelligence (AI) adoption focus on its adoption at the individual task level. What has received significantly less attention is how AI adoption is shaped by the fact that organizations are composed of many interacting tasks. AI adoption may, therefore, require system‐wide change, which is both a constraint and an opportunity. We provide the first formal analysis where multiple tasks may be part of an interdependent system. We find that reliance on AI, a prediction tool, increases decision variation, which, in turn, raises challenges if decisions across the organization interact. Reducing inter‐dependencies between decisions softens that impact and can facilitate AI adoption. However, it does this at the expense of synergies. By contrast, when there are mechanisms for inter‐decision coordination, AI adoption is enhanced when there are more inter‐dependencies. Consequently, we show that there are important cases where AI adoption will be enhanced when it can be adopted beyond tasks but as part of a designed organizational system.

Suggested Citation

  • Ajay Agrawal & Joshua S. Gans & Avi Goldfarb, 2024. "Artificial intelligence adoption and system‐wide change," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 33(2), pages 327-337, March.
    • Handle: RePEc:bla:jemstr:v:33:y:2024:i:2:p:327-337
    DOI: 10.1111/jems.12521
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    References listed on IDEAS

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    2. Guillermo Arenas Díaz & Mariacristina Piva & Marco Vivarelli, 2025. "Artificial intelligence as a method of invention," DISCE - Working Papers del Dipartimento di Politica Economica dipe0052, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    3. Aaron Chatterji & Daniel Rock & Eduard Talamas, 2025. "Transformative AI and Firms," NBER Chapters, in: The Economics of Transformative AI, National Bureau of Economic Research, Inc.
    4. Pascal Stiefenhofer, 2025. "Artificial General Intelligence and the Social Contract: A Dynamic Political Economy Model," Journal of Economic Analysis, Anser Press, vol. 4(3), pages 142-183, September.
    5. Xienan Cheng & Mustafa Dogan & Pinar Yildirim, 2025. "Artificial Intelligence in Team Dynamics: Who Gets Replaced and Why?," Papers 2506.12337, arXiv.org, revised Mar 2026.
    6. Alex Farach & Alexia Cambon & Lev Tankelevitch & Connie Hsueh & Rebecca Janssen, 2026. "Scaffolding Human-AI Collaboration: A Field Experiment on Behavioral Protocols and Cognitive Reframing," Papers 2604.08678, arXiv.org, revised Apr 2026.
    7. Kristina McElheran & Mu-Jeung Yang & Zachary Kroff & Erik Brynjolfsson, 2025. "The Rise of Industrial AI in America: Microfoundations of the Productivity J-curve(s)," Working Papers 25-27, Center for Economic Studies, U.S. Census Bureau.

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