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Predictive AI and productivity growth dynamics: Evidence from French firms

Author

Listed:
  • Luca Fontanelli

    (UniBs - Università degli Studi di Brescia = University of Brescia, CMCC - Euro-Mediterranean Center on Climate Change, RFF-CMCC European Institute on Economics and the Environment (Milan))

  • Mattia Guerini

    (UniBs - Università degli Studi di Brescia = University of Brescia, FEEM - Fondazione Eni Enrico Mattei [Milano])

  • Raffaele Miniaci

    (UniBs - Università degli Studi di Brescia = University of Brescia)

  • Angelo Secchi

    (CMCC - Euro-Mediterranean Center on Climate Change, RFF-CMCC European Institute on Economics and the Environment (Milan), 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 - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - ENPC - École nationale des ponts et chaussées - IP Paris - Institut Polytechnique de Paris, 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 - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - ENPC - École nationale des ponts et chaussées - IP Paris - Institut Polytechnique de Paris)

Abstract

While artificial intelligence (AI) adoption holds the potential to enhance business operations through improved forecasting and automation, its relation with average productivity growth remain highly heterogeneous across firms. This paper shifts the focus and investigates the impact of predictive artificial intelligence (AI) on the volatility of firms' productivity growth r ates. Using firm-level data from the 2019 French ICT survey, we provide robust evidence that AI use is associated with increased volatility. This relationship persists across multiple robustness checks, including analyses addressing causality concerns. To propose a possible mechanisms underlying this effect, we compare firms that purchase AI from external providers ("AI buyers") and those that develop AI in-house ("AI developers"). Our results show that heightened volatility is concentrated among AI buyers, whereas firms that develop AI internally experience no such effect. Finally, we find that AI-induced volatility among "AI buyers" is mitigated in firms with a higher share of ICT engineers and technicians, suggesting that AI's successful integration requires complementary human capital.

Suggested Citation

  • Luca Fontanelli & Mattia Guerini & Raffaele Miniaci & Angelo Secchi, 2025. "Predictive AI and productivity growth dynamics: Evidence from French firms," Post-Print halshs-05368544, HAL.
    • Handle: RePEc:hal:journl:halshs-05368544
    DOI: 10.2139/ssrn.5219549
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    JEL classification:

    • D20 - Microeconomics - - Production and Organizations - - - General
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • 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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