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How Different Uses of AI Shape Labor Demand: Evidence from France

Author

Listed:
  • Philippe Aghion

    (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, CdF (institution) - Collège de France)

  • Simon Bunel

    (INSEE - Institut national de la statistique et des études économiques (INSEE), Centre de recherche de la Banque de France - Banque de France, CdF (institution) - Collège de France)

  • Xavier Jaravel

    (LSE - London School of Economics and Political Science, CEPR - Center for Economic Policy Research)

  • Thomas Mikaelsen

    (Stockholm University)

  • Alexandra Roulet

    (CEPR - Center for Economic Policy Research, INSEAD - Institut Européen d'administration des Affaires)

  • Jakob Søgaard

    (UCPH - University of Copenhagen = Københavns Universitet)

Abstract

Using French firm-level data on AI adoption from 2017-2020, we find that, first, firms adopting AI are larger and more productive and skill intensive. Second, difference-in-difference estimates reveal an increase in firm-level employment and sales after AI adoption, suggesting that the induced productivity gains allow firms to grow and outweigh potential displacement effects. Third, occupations classified in recent work as substitutable with AI expand. Fourth, AI usage is a relevant dimension of heterogeneity in the labor demand response: We find positive employment growth for certain uses (e.g., information and communications technology security) and negative for others (e.g., administrative processes).

Suggested Citation

  • Philippe Aghion & Simon Bunel & Xavier Jaravel & Thomas Mikaelsen & Alexandra Roulet & Jakob Søgaard, 2025. "How Different Uses of AI Shape Labor Demand: Evidence from France," Post-Print halshs-05144088, HAL.
    • Handle: RePEc:hal:journl:halshs-05144088
    DOI: 10.1257/pandp.20251047
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    References listed on IDEAS

    as
    1. Daron Acemoglu & David Autor & Jonathon Hazell & Pascual Restrepo, 2022. "Artificial Intelligence and Jobs: Evidence from Online Vacancies," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 293-340.
    2. Domini, Giacomo & Grazzi, Marco & Moschella, Daniele & Treibich, Tania, 2021. "Threats and opportunities in the digital era: Automation spikes and employment dynamics," Research Policy, Elsevier, vol. 50(7).
    3. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    4. Jay Dixon & Bryan Hong & Lynn Wu, 2021. "The Robot Revolution: Managerial and Employment Consequences for Firms," Management Science, INFORMS, vol. 67(9), pages 5586-5605, September.
    5. Carlo Pizzinelli & Augustus J Panton & Ms. Marina Mendes Tavares & Mauro Cazzaniga & Longji Li, 2023. "Labor Market Exposure to AI: Cross-country Differences and Distributional Implications," IMF Working Papers 2023/216, International Monetary Fund.
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    Cited by:

    1. Gustavo de Souza, 2025. "Artificial Intelligence in the Office and the Factory: Evidence from Administrative Software Registry Data," Working Paper Series WP 2025-11, Federal Reserve Bank of Chicago.

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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
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • M51 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Firm Employment Decisions; Promotions
    • 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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