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Firm Data on AI

Author

Listed:
  • Jose Maria Barrero

    (Instituto Tecnologico Autonomo de Mexico (ITAM))

  • Nicholas Bloom

    (Stanford University)

  • Philip Bunn

    (Bank of England)

  • Steven J. Davis

    (University of Chicago)

  • Kevin Foster

    (Federal Reserve Bank of Atlanta)

  • Aaron Jalca

    (Federal Reserve Bank of Atlanta)

  • Brent Meyer

    (Federal Reserve Bank of Atlanta)

  • Paul Mizen

    (King’s College London)

  • Michael A. Navarrete

    (Federal Reserve Bank of Atlanta)

  • Pawel Smietanka

    (Deutsche Bundesbank)

  • Gregory Thwaites

    (University of Nottingham)

  • Ben Zhe Wang

    (Macquarie University)

  • Ivan Yotzov

    (Bank of England)

Abstract

We survey nearly 6,000 senior business executives at US, UK, German, and Australian firms to develop new evidence on AI adoption and its effects on jobs, productivity, and output. Specifically, we ask executives about AI usage, its effects at their own firms over the past three years and, looking ahead, what they anticipate over the next three years. We find four main results. First, 69% of firms actively use AI, with higher usage rates at younger and more productive firms. Second, more than two thirds of executives regularly use AI, but their usage rate averages only 1.5 hours a week. Third, executives report little own-firm impact of AI over the last 3 years, with nine-in-ten reporting no impact on employment or productivity. Fourth, these same executives predict sizable effects over the next 3 years, predicting that AI will boost productivity at their firms by an average of 1.4%, raise output 0.8%, and cut employment 0.7%. In contrast, employees anticipate that AI will raise employment 0.5% at their firms in the next 3 years, highlighting an expectations gap between employers and Employees.

Suggested Citation

  • Jose Maria Barrero & Nicholas Bloom & Philip Bunn & Steven J. Davis & Kevin Foster & Aaron Jalca & Brent Meyer & Paul Mizen & Michael A. Navarrete & Pawel Smietanka & Gregory Thwaites & Ben Zhe Wang &, 2026. "Firm Data on AI," Working Papers 2026-47, Becker Friedman Institute for Research In Economics.
  • Handle: RePEc:bfi:wpaper:2026-47
    as

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    File URL: https://repec.bfi.uchicago.edu/RePEc/pdfs/BFI_WP_2026-47.pdf
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    Other versions of this item:

    • 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.
    • 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.

    More about this item

    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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