IDEAS home Printed from https://ideas.repec.org/p/unm/unumer/2025016.html
   My bibliography  Save this paper

Does Training in AI Affect PhD Students’ Careers? Evidence from France

Author

Listed:
  • Boutros, Pierre
  • Diodati, Eliana
  • Pezzoni, Michele
  • Visentin, Fabiana

    (RS: GSBE other - not theme-related research, Mt Economic Research Inst on Innov/Techn)

Abstract

The rise of Artificial Intelligence (AI) urges us to better understand its impact on the labor market. This paper is the first to analyze the supply of individuals with AI training facing the labor market. We estimate the relationship between AI training and individuals’ careers for 35,492 French PhD students in STEM who graduated between 2010 and 2018. To assess the unbiased effect of AI training, we compare the careers of PhD students trained in AI with those of a control sample of similar students with no AI training. We find that AI training is not associated with a higher probability of pursuing a research career after graduation. However, among students who have AI training during the PhD and pursue a research career after graduation, we observe a path dependence in continuing to publish on AI topics and a higher impact of their research. We also observe disciplinary heterogeneity. In Computer Science, AI-trained students are less likely to end up in private research organizations after graduation compared to their non-AI counterparts, while in disciplines other than Computer Science, AI training stimulates patenting activity and mobility abroad after graduation.

Suggested Citation

  • Boutros, Pierre & Diodati, Eliana & Pezzoni, Michele & Visentin, Fabiana, 2025. "Does Training in AI Affect PhD Students’ Careers? Evidence from France," MERIT Working Papers 2025-016, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    • Handle: RePEc:unm:unumer:2025016
    DOI: 10.53330/EPFW4463
    as

    Download full text from publisher

    File URL: https://cris.maastrichtuniversity.nl/ws/files/265822712/wp2025-016.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.53330/EPFW4463?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
    ---><---

    References listed on IDEAS

    as
    1. Dror Shvadron & Hansen Zhang & Lee Fleming & Daniel P. Gross, 2025. "Funding the U.S. Scientific Training Ecosystem: New Data, Methods, and Evidence," NBER Working Papers 33944, National Bureau of Economic Research, Inc.
    2. Henry Sauermann & Paula Stephan, 2013. "Conflicting Logics? A Multidimensional View of Industrial and Academic Science," Organization Science, INFORMS, vol. 24(3), pages 889-909, June.
    3. Shibayama, Sotaro, 2019. "Sustainable development of science and scientists: Academic training in life science labs," Research Policy, Elsevier, vol. 48(3), pages 676-692.
    4. Mariagrazia Squicciarini & Heike Nachtigall, 2021. "Demand for AI skills in jobs: Evidence from online job postings," OECD Science, Technology and Industry Working Papers 2021/03, OECD Publishing.
    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. Wang, Jian & Shibayama, Sotaro, 2022. "Mentorship and creativity: Effects of mentor creativity and mentoring style," Research Policy, Elsevier, vol. 51(3).
    2. Ryazanova, Olga & Jaskiene, Jolanta, 2022. "Managing individual research productivity in academic organizations: A review of the evidence and a path forward," Research Policy, Elsevier, vol. 51(2).
    3. Hottenrott, Hanna & Lawson, Cornelia, 2014. "Flying the nest: How the home department shapes researchers’ career paths," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 201409, University of Turin.
    4. Hoekman, Jarno & Rake, Bastian, 2024. "Geography of authorship: How geography shapes authorship attribution in big team science," Research Policy, Elsevier, vol. 53(2).
    5. Saima Javed & Yu Rong & Babar Nawaz Abbasi, 2024. "Convergence analysis of artificial intelligence research capacity: Are the less developed catching up with the developed ones?," Journal of International Development, John Wiley & Sons, Ltd., vol. 36(4), pages 2172-2192, May.
    6. Carolin Haeussler & Henry Sauermann, 2016. "The Division of Labor in Teams: A Conceptual Framework and Application to Collaborations in Science," NBER Working Papers 22241, National Bureau of Economic Research, Inc.
    7. Llopis, Oscar & D'Este, Pablo & McKelvey, Maureen & Yegros, Alfredo, 2022. "Navigating multiple logics: Legitimacy and the quest for societal impact in science," Technovation, Elsevier, vol. 110(C).
    8. Sofia Patsali & Michele Pezzoni & Fabiana Visentin, 2021. "The Impact of Research Independence on PhD Students’ Careers: Large-Scale Evidence from France," Post-Print hal-03564708, HAL.
    9. Ener, Hakan, 2022. "How does CEO technical expertise influence licensing-out at technology ventures?," Technovation, Elsevier, vol. 114(C).
    10. Gans, Joshua S. & Murray, Fiona E. & Stern, Scott, 2017. "Contracting over the disclosure of scientific knowledge: Intellectual property and academic publication," Research Policy, Elsevier, vol. 46(4), pages 820-835.
    11. Jeongeun Kim & Molly Ott & Lindsey Dippold, 2020. "University and Department Influences on Scientists’ Occupational Outcomes," Research in Higher Education, Springer;Association for Institutional Research, vol. 61(2), pages 197-228, March.
    12. Koehler, Maximilian & Sauermann, Henry, 2024. "Algorithmic management in scientific research," Research Policy, Elsevier, vol. 53(4).
    13. Usabiaga, Carlos & Núñez, Fernando & Arendt, Lukasz & Gałecka-Burdziak, Ewa & Pater, Robert, 2022. "Skill requirements and labour polarisation: An association analysis based on Polish online job offers," Economic Modelling, Elsevier, vol. 115(C).
    14. Farhat Chowdhury & Albert N Link & Martijn van Hasselt, 2022. "The spatial distribution of public support for AI research [Agglomeration and Productivity: Evidence from Firm-Level Data]," Science and Public Policy, Oxford University Press, vol. 49(4), pages 573-579.
    15. Liu, Xing & Wu, Xianhua & Zhang, Weipan, 2024. "A new DEA model and its application in performance evaluation of scientific research activities in the universities of China's double first-class initiative," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    16. Fagateanu Alina-Mihaela & Nicolaescu Sergiu Ştefan & Kifor Claudiu Vasile & Mărginean Silvia, 2015. "Student Career Management – Private and Public Sector Involvement," Balkan Region Conference on Engineering and Business Education, Sciendo, vol. 1(1), pages 1-9, November.
    17. Kiri, Bralind & Lacetera, Nicola & Zirulia, Lorenzo, 2018. "Above a swamp: A theory of high-quality scientific production," Research Policy, Elsevier, vol. 47(5), pages 827-839.
    18. Ricciardi, Francesca & De Bernardi, Paola & Cantino, Valter, 2020. "System dynamics modeling as a circular process: The smart commons approach to impact management," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    19. Clayton, Paige & Lanahan, Lauren & Nelson, Andrew, 2022. "Dissecting diffusion: Tracing the plurality of factors that shape knowledge diffusion," Research Policy, Elsevier, vol. 51(1).
    20. McCabe, Angela & Parker, Rachel & Osegowitsch, Tom & Cox, Stephen, 2023. "Overcoming barriers to knowledge co-production in academic–practitioner research collaboration," European Management Journal, Elsevier, vol. 41(2), pages 212-222.

    More about this item

    JEL classification:

    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

    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:unm:unumer:2025016. 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: Ad Notten The email address of this maintainer does not seem to be valid anymore. Please ask Ad Notten to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/meritnl.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.