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The Adoption of Industrial AI in America

Author

Listed:
  • Kristina McElheran
  • Mu-Jeung Yang
  • Zachary Kroff
  • Erik Brynjolfsson

Abstract

Using a mandatory, purpose-designed Census Bureau survey of approximately 28,500 establishments, we provide new evidence on industrial AI adoption in US manufacturing. Despite widespread digitization, only 22.8 percent of plants report any AI use as of 2021; intensity-weighted adoption is far lower. Adoption correlates with more-recent digital infrastructure—cloud computing and predictive analytics—rather than legacy on-premises IT or descriptive analytics. Structured production-process management and size are significant predictors. Cost and lack of applicable use case are the most cited barriers, followed by expertise. Prior productivity does not predict use, pointing to organizational readiness as a key barrier to AI diffusion.

Suggested Citation

  • Kristina McElheran & Mu-Jeung Yang & Zachary Kroff & Erik Brynjolfsson, 2026. "The Adoption of Industrial AI in America," AEA Papers and Proceedings, American Economic Association, vol. 116, pages 20-25, May.
    • Handle: RePEc:aea:apandp:v:116:y:2026:p:20-25
    DOI: 10.1257/pandp.20261033
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    More about this item

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • 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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