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Firm Data on AI

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Abstract

We present the first representative international data on firm-level AI use. We survey almost 6,000 CFOs, CEOs, and executives from stratified firm samples across the US, UK, Germany, and Australia. We find four key facts. First, around 70 percent of firms actively use AI, particularly younger, more productive firms. Second, while over two-thirds of top executives regularly use AI, their average use is only 1.5 hours a week, with one quarter reporting no AI use. Third, firms report little impact of AI over the last three years, with more than 80 percent of firms reporting no impact on either employment or productivity. Fourth, firms predict sizable impacts over the next three years, forecasting AI will boost productivity by 1.4 percent, increase output by 0.8 percent, and cut employment by 0.7 percent. We also survey individual employees who predict a 0.5 percent increase in employment in the next three years as a result of AI. This contrast implies a sizable gap in expectations, with senior executives predicting reductions in employment from AI and employees predicting net job creation.

Suggested Citation

  • Jose Maria Barrero & Nicholas Bloom & Philip Bunn & Steven J. Davis & Kevin Foster & Aaron Jalca & Brent Meyer & Paul Mizen & Michael Navarrete & Pawel Smietanka & Gregory Thwaites & Ben Wang & Ivan Y, 2026. "Firm Data on AI," FRB Atlanta Working Paper 2026-3, Federal Reserve Bank of Atlanta.
  • Handle: RePEc:fip:fedawp:102928
    DOI: 10.29338/wp2026-03
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    Other versions of this item:

    • Ivan Yotzov & Jose Maria Barrero & Nicholas Bloom & Philip Bunn & Steven J. Davis & Kevin M. Foster & Aaron Jalca & Brent H. Meyer & Paul Mizen & Michael A. Navarrete & Pawel Smietanka & Gregory Thwai, 2026. "Firm Data on AI," NBER Working Papers 34836, National Bureau of Economic Research, Inc.

    References listed on IDEAS

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    1. Daron Acemoglu, 2025. "The simple macroeconomics of AI," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 40(121), pages 13-58.
    2. Teutloff, Ole & Einsiedler, Johanna & Kässi, Otto & Braesemann, Fabian & Mishkin, Pamela & del Rio-Chanona, R. Maria, 2025. "Winners and losers of generative AI: Early Evidence of Shifts in Freelancer Demand," Journal of Economic Behavior & Organization, Elsevier, vol. 235(C).
    3. Bell, Andrew M. & Gift, Thomas, 2023. "Fraud in Online Surveys: Evidence from a Nonprobability, Subpopulation Sample – ADDENDUM," Journal of Experimental Political Science, Cambridge University Press, vol. 10(1), pages 154-154, March.
    4. Jaison R. Abel & Richard Deitz & Natalia Emanuel & Benjamin Hyman, 2024. "AI and the Labor Market: Will Firms Hire, Fire, or Retrain?," Liberty Street Economics 20240904b, Federal Reserve Bank of New York.
    5. Kathryn Bonney & Cory Breaux & Catherine Buffington & Emin Dinlersoz & Lucia Foster & Nathan Goldschlag & John Haltiwanger & Zachary Kroff & Keith Savage, 2024. "Tracking Firm Use of AI in Real Time: A Snapshot from the Business Trends and Outlook Survey," Working Papers 24-16, Center for Economic Studies, U.S. Census Bureau.
    6. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    7. Bell, Andrew M. & Gift, Thomas, 2023. "Fraud in Online Surveys: Evidence from a Nonprobability, Subpopulation Sample," Journal of Experimental Political Science, Cambridge University Press, vol. 10(1), pages 148-153, March.
    8. Ian Goldin & Pantelis Koutroumpis & François Lafond & Julian Winkler, 2024. "Why Is Productivity Slowing Down?," Journal of Economic Literature, American Economic Association, vol. 62(1), pages 196-268, March.
    9. Altig, David & Barrero, Jose Maria & Bloom, Nicholas & Davis, Steven J. & Meyer, Brent & Parker, Nicholas, 2022. "Surveying business uncertainty," Journal of Econometrics, Elsevier, vol. 231(1), pages 282-303.
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    • E0 - Macroeconomics and Monetary Economics - - General

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