IDEAS home Printed from https://ideas.repec.org/p/ags/feemwp/355806.html
   My bibliography  Save this paper

Predictive AI and productivity growth dynamics: evidence from French firms

Author

Listed:
  • Fontanelli, Luca
  • Guerini, Mattia
  • Miniaci, Raffaele
  • Secchi, Angelo

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 rates. 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

  • Fontanelli, Luca & Guerini, Mattia & Miniaci, Raffaele & Secchi, Angelo, 2025. "Predictive AI and productivity growth dynamics: evidence from French firms," FEEM Working Papers 355806, Fondazione Eni Enrico Mattei (FEEM).
  • Handle: RePEc:ags:feemwp:355806
    DOI: 10.22004/ag.econ.355806
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/355806/files/NDL2025-11-1.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.355806?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Fontanelli, Luca & Guerini, Mattia & Napoletano, Mauro, 2023. "International trade and technological competition in markets with dynamic increasing returns," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    2. Erik Brynjolfsson & Daniel Rock & Chad Syverson, 2021. "The Productivity J-Curve: How Intangibles Complement General Purpose Technologies," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(1), pages 333-372, January.
    3. J.J. Harrigan & Ariell Reshef & Farid Toubal, 2023. "Techies and Firm Level Productivity," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-04429434, HAL.
    4. Nathan Rosenberg, 2009. "Uncertainty and Technological Change," World Scientific Book Chapters, in: Nathan Rosenberg (ed.), Studies On Science And The Innovation Process Selected Works of Nathan Rosenberg, chapter 8, pages 153-172, World Scientific Publishing Co. Pte. Ltd..
    5. Charles Hoffreumon & Chris Forman & Nicolas van Zeebroeck, 2024. "Make or buy your artificial intelligence? Complementarities in technology sourcing," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 33(2), pages 452-479, March.
    6. Giulio Bottazzi & Angelo Secchi, 2006. "Gibrat's Law and diversification," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 15(5), pages 847-875, October.
    7. Kristina McElheran & J. Frank Li & Erik Brynjolfsson & Zachary Kroff & Emin Dinlersoz & Lucia Foster & Nikolas Zolas, 2024. "AI adoption in America: Who, what, and where," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 33(2), pages 375-415, March.
    8. Timothy F. Bresnahan & Erik Brynjolfsson & Lorin M. Hitt, 2002. "Information Technology, Workplace Organization, and the Demand for Skilled Labor: Firm-Level Evidence," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(1), pages 339-376.
    9. repec:osf:socarx:v3cgs_v1 is not listed on IDEAS
    10. Babina, Tania & Fedyk, Anastassia & He, Alex & Hodson, James, 2024. "Artificial intelligence, firm growth, and product innovation," Journal of Financial Economics, Elsevier, vol. 151(C).
    11. Iacus, Stefano M. & King, Gary & Porro, Giuseppe, 2011. "Multivariate Matching Methods That Are Monotonic Imbalance Bounding," Journal of the American Statistical Association, American Statistical Association, vol. 106(493), pages 345-361.
    12. Jovanovic, Boyan, 1982. "Selection and the Evolution of Industry," Econometrica, Econometric Society, vol. 50(3), pages 649-670, May.
    13. Erik Brynjolfsson & Lorin M. Hitt, 2003. "Computing Productivity: Firm-Level Evidence," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 793-808, November.
    14. Calvino, Flavio & Criscuolo, Chiara & Menon, Carlo & Secchi, Angelo, 2018. "Growth volatility and size: A firm-level study," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 390-407.
    15. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    16. Tyna Eloundou & Sam Manning & Pamela Mishkin & Daniel Rock, 2023. "GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models," Papers 2303.10130, arXiv.org, revised Aug 2023.
    17. Alekseeva, Liudmila & Azar, José & Giné, Mireia & Samila, Sampsa & Taska, Bledi, 2021. "The demand for AI skills in the labor market," Labour Economics, Elsevier, vol. 71(C).
    18. Bianchini, Stefano & Müller, Moritz & Pelletier, Pierre, 2022. "Artificial intelligence in science: An emerging general method of invention," Research Policy, Elsevier, vol. 51(10).
    19. Kreitmeir, David & Raschky, Paul Anton, 2023. "The Unintended Consequences of Censoring Digital Technology - Evidence from Italy's ChatGPT Ban," SocArXiv v3cgs, Center for Open Science.
    20. Stefano Bianchini & Moritz Müller & Pierre Pelletier, 2022. "Artificial intelligence in science: An emerging general method of invention," Post-Print hal-03958025, HAL.
    21. Erzo G. J. Luttmer, 2007. "Selection, Growth, and the Size Distribution of Firms," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(3), pages 1103-1144.
    22. Tania Babina & Anastassia Fedyk & Alex X. He & James Hodson, 2023. "Firm Investments in Artificial Intelligence Technologies and Changes in Workforce Composition," NBER Working Papers 31325, National Bureau of Economic Research, Inc.
    23. Wooldridge, Jeffrey M., 2009. "On estimating firm-level production functions using proxy variables to control for unobservables," Economics Letters, Elsevier, vol. 104(3), pages 112-114, September.
    24. Tania Babina & Anastassia Fedyk & Alex X. He & James Hodson, 2023. "Firm Investments in Artificial Intelligence Technologies and Changes in Workforce Composition," NBER Chapters, in: Technology, Productivity, and Economic Growth, National Bureau of Economic Research, Inc.
    25. Marioni, Larissa da Silva & Rincon-Aznar, Ana & Venturini, Francesco, 2024. "Productivity performance, distance to frontier and AI innovation: Firm-level evidence from Europe," Journal of Economic Behavior & Organization, Elsevier, vol. 228(C).
    26. Giacomo Damioli & Vincent Van Roy & Daniel Vertesy, 2021. "The impact of artificial intelligence on labor productivity," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 11(1), pages 1-25, March.
    27. Flavio Calvino & Luca Fontanelli, 2024. "AI Users Are Not All Alike: The Characteristics of French Firms Buying and Developing AI," CESifo Working Paper Series 11466, CESifo.
    28. Iacus, Stefano M. & King, Gary & Porro, Giuseppe, 2012. "Causal Inference without Balance Checking: Coarsened Exact Matching," Political Analysis, Cambridge University Press, vol. 20(1), pages 1-24, January.
    29. Hopenhayn, Hugo A, 1992. "Entry, Exit, and Firm Dynamics in Long Run Equilibrium," Econometrica, Econometric Society, vol. 60(5), pages 1127-1150, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Flavio Calvino & Luca Fontanelli, 2025. "Decoding AI: Nine facts about how firms use artificial intelligence in France," LEM Papers Series 2025/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    2. Flavio Calvino & Luca Fontanelli, 2024. "AI Users Are Not All Alike: The Characteristics of French Firms Buying and Developing AI," CESifo Working Paper Series 11466, CESifo.
    3. Luca Fontanelli & Flavio Calvino & Chiara Criscuolo & Lionel Nesta & Elena Verdolini, 2024. "The role of human capital for AI adoption: Evidence from French firms," Post-Print hal-05029748, HAL.
    4. Flavio Calvino & Luca Fontanelli, 2023. "Artificial intelligence, complementary assets and productivity: evidence from French firms," LEM Papers Series 2023/35, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    5. Kristina McElheran & J. Frank Li & Erik Brynjolfsson & Zachary Kroff & Emin Dinlersoz & Lucia Foster & Nikolas Zolas, 2024. "AI adoption in America: Who, what, and where," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 33(2), pages 375-415, March.
    6. Fontanelli, Luca & Guerini, Mattia & Napoletano, Mauro, 2023. "International trade and technological competition in markets with dynamic increasing returns," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    7. Charles Hoffreumon & Chris Forman & Nicolas van Zeebroeck, 2024. "Make or buy your artificial intelligence? Complementarities in technology sourcing," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 33(2), pages 452-479, March.
    8. Luca Fontanelli, 2023. "Theories of market selection: a survey," LEM Papers Series 2023/22, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    9. Tao Chen & Shuwen Pi & Qing Sophie Wang, 2025. "Artificial Intelligence and Corporate Investment Efficiency: Evidence from Chinese Listed Companies," Working Papers in Economics 25/05, University of Canterbury, Department of Economics and Finance.
    10. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    11. Jeffrey L. Furman & Florenta Teodoridis, 2020. "Automation, Research Technology, and Researchers’ Trajectories: Evidence from Computer Science and Electrical Engineering," Organization Science, INFORMS, vol. 31(2), pages 330-354, March.
    12. Li, Shengyu, 2018. "A structural model of productivity, uncertain demand, and export dynamics," Journal of International Economics, Elsevier, vol. 115(C), pages 1-15.
    13. Giulio Bottazzi & Taewon Kang & Federico Tamagni, 2023. "Persistence in firm growth: inference from conditional quantile transition matrices," Small Business Economics, Springer, vol. 61(2), pages 745-770, August.
    14. Giovanni Dosi & Daniele Moschella & Emanuele Pugliese & Federico Tamagni, 2015. "Productivity, market selection, and corporate growth: comparative evidence across US and Europe," Small Business Economics, Springer, vol. 45(3), pages 643-672, October.
    15. Stefano Bianchini & Giulio Bottazzi & Federico Tamagni, 2017. "What does (not) characterize persistent corporate high-growth?," Small Business Economics, Springer, vol. 48(3), pages 633-656, March.
    16. Fossen, Frank M. & McLemore, Trevor & Sorgner, Alina, 2024. "Artificial Intelligence and Entrepreneurship," IZA Discussion Papers 17055, Institute of Labor Economics (IZA).
    17. Torrent-Sellens, Joan, 2024. "Digital transition, data-and-tasks crowd-based economy, and the shared social progress: Unveiling a new political economy from a European perspective," Technology in Society, Elsevier, vol. 79(C).
    18. Satyajit Chatterjee & Esteban Rossi‐Hansberg, 2012. "Spinoffs And The Market For Ideas," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(1), pages 53-93, February.
    19. Cristina Fernández & Roberta García & Paloma Lopez-Garcia & Benedicta Marzinotto & Roberta Serafini & Juuso Vanhala & Ladislav Wintr, 2017. "Firm growth in Europe: An overview based on the COMPNET labour module," BCL working papers 107, Central Bank of Luxembourg.
    20. Barth, Erling & Davis, James C. & Freeman, Richard B. & McElheran, Kristina, 2023. "Twisting the demand curve: Digitalization and the older workforce," Journal of Econometrics, Elsevier, vol. 233(2), pages 443-467.

    More about this item

    Keywords

    Dairy Farming; Production Economics; Research and Development/Tech Change/Emerging Technologies; Resource/Energy Economics and Policy;
    All these keywords.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:feemwp:355806. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/feemmit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.