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Artificial Intelligence and Jobs: Evidence from US Commuting Zones

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  • Bonfiglioli, Alessandra
  • Crinò, Rosario
  • Gancia, Gino
  • Papadakis, Ioannis

Abstract

We study the effect of Artificial Intelligence (AI) on employment across US commuting zones over the period 2000-2020. A simple model shows that AI can automate jobs or complement workers, and illustrates how to estimate its effect by exploiting variation in a novel measure of local exposure to AI: job growth in AI-related professions built from detailed occupational data. Using a shift-share instrument that combines industry-level AI adoption with local industry employment, we estimate robust negative effects of AI exposure on employment across commuting zones and time. We find that AI's impact is different from other capital and technologies, and that it works through services more than manufacturing. Moreover, the employment effect is especially negative for low-skill and production workers, while it turns positive for workers at the top of the wage distribution and for those in STEM occupations. These results are consistent with the view that AI has contributed to the automation of jobs and to widen inequality.

Suggested Citation

  • Bonfiglioli, Alessandra & Crinò, Rosario & Gancia, Gino & Papadakis, Ioannis, 2023. "Artificial Intelligence and Jobs: Evidence from US Commuting Zones," CEPR Discussion Papers 18495, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:18495
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    Cited by:

    1. is not listed on IDEAS
    2. Christina Gathmann & Felix Grimm & Erwin Winkler, 2024. "AI, Task Changes in Jobs, and Worker Reallocation," CESifo Working Paper Series 11585, CESifo.
    3. Guarascio, Dario & Reljic, Jelena, 2025. "AI and employment in Europe," Economics Letters, Elsevier, vol. 247(C).
    4. Alessandra Bonfiglioli & Rosario Crinò & Mattia Filomena & Gino Gancia, 2025. "Data, Power and Emissions: The Environmental Cost of AI," CESifo Working Paper Series 12158, CESifo.
    5. Minniti, Antonio & Prettner, Klaus & Venturini, Francesco, 2025. "AI innovation and the labor share in European regions," European Economic Review, Elsevier, vol. 177(C).
    6. Spreen, Thomas Luke & Wang, Ziyuan & Yang, Lang (Kate), 2025. "Industrial automation and local public goods," Journal of Public Economics, Elsevier, vol. 247(C).
    7. Liu, Yan & Wang, He & Yu, Shu, 2025. "Labor Demand in the Age of Generative AI : Early Evidence from the U.S. Job Posting Data," Policy Research Working Paper Series 11263, The World Bank.
    8. Carlo Drago & Alberto Costantiello & Marco Savorgnan & Angelo Leogrande, 2025. "Driving AI Adoption in the EU: A Quantitative Analysis of Macroeconomic Influences," Working Papers hal-05102974, HAL.
    9. Engberg, Erik & Koch, Michael & Lodefalk, Magnus & Schroeder, Sarah, 2025. "Artificial intelligence, tasks, skills, and wages: Worker-level evidence from Germany," Research Policy, Elsevier, vol. 54(8).
    10. Stefania Albanesi & António Dias da Silva & Juan F Jimeno & Ana Lamo & Alena Wabitsch, 2025. "New technologies and jobs in Europe," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 40(121), pages 71-139.
    11. Alessandra Bonfiglioli & Rosario Crinò & Mattia Filomena & Gino Gancia, 2025. "Comparative Advantage in AI-Intensive Industries: Evidence from US Imports," CESifo Working Paper Series 11642, CESifo.

    More about this item

    JEL classification:

    • 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
    • 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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