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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
  • Xavier Jaravel
  • Thomas Mikaelsen
  • Alexandra Roulet
  • Jakob Søgaard

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," PSE-Ecole d'économie de Paris (Postprint) halshs-05144088, HAL.
    • Handle: RePEc:hal:pseptp:halshs-05144088
    DOI: 10.1257/pandp.20251047
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