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AI Adoption and System-Wide Change

Author

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

Abstract

Analyses of 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 organisations 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 a modular or non-modular system. We find that reliance on AI, a prediction tool, increases decision variation which, in turn, raises challenges if decisions across the organisation interact. Modularity, which leads to task independence rather than system-level inter-dependencies, softens that impact. Thus, modularity 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 is a non-modular environment. 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 organisational system.

Suggested Citation

  • Ajay K. Agrawal & Joshua S. Gans & Avi Goldfarb, 2021. "AI Adoption and System-Wide Change," NBER Working Papers 28811, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:28811
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    Cited by:

    1. Tyna Eloundou & Sam Manning & Pamela Mishkin & Daniel Rock, 2023. "GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models," Papers 2303.10130, arXiv.org, revised Aug 2023.
    2. Bäck, Asta & Hajikhani, Arash & Jäger, Angela & Schubert, Torben & Suominen, Arho, 2022. "Return of the Solow-paradox in AI? AI-adoption and firm productivity," Papers in Innovation Studies 2022/1, Lund University, CIRCLE - Centre for Innovation Research.
    3. Klügl, Franziska & Kyvik Nordås, Hildegunn, 2021. "AI-enabled Automation, Trade, and the Future of Engineering Services," Working Papers 2021:16, Örebro University, School of Business.
    4. Joshua S. Gans, 2023. "Artificial intelligence adoption in a monopoly market," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(2), pages 1098-1106, March.

    More about this item

    JEL classification:

    • M1 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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