IDEAS home Printed from https://ideas.repec.org/p/iso/educat/0251.html

Generative AI and Career Choices

Author

Listed:
  • Christian Gschwendt
  • Martina Viarengo
  • Thea S. Zoellner

Abstract

The economic impact of technological change will critically depend on how future workers invest in their human capital. Yet, little is known about how future workers themselves evaluate and choose their educational and occupational paths in light of emerging technologies. This paper examines how adolescents currently at the school-to-work transition stage value working with generative artificial intelligence (GenAI) in their future occupations, and how automation risk and opportunities for continuing education shape these preferences. We field a discrete-choice experiment among a nationally representative sample of over 7,000 Swiss adolescents aged around 15. We find that adolescents generally exhibit an aversion to collaborating with GenAI at work, with females consistently more averse than males. However, preferences are nuanced: adolescents welcome greater GenAI collaboration, provided that GenAI usage levels remain moderate and that it is not accompanied by increases in job-automation risk. Finally, continuing education opportunities in occupations improve attitudes towards working with GenAI across genders. Our results challenge simple narratives of technology acceptance or rejection, revealing that adolescents' willingness to work with GenAI depends on how it is implemented — its intensity, associated displacement risks, and accompanying skill development - rather than the technology itself. Our findings suggest that the way future workers value GenAI collaboration in their career choices critically depends on its intensity and on the interplay with automation risk and AI-related educational opportunities.

Suggested Citation

  • Christian Gschwendt & Martina Viarengo & Thea S. Zoellner, 2026. "Generative AI and Career Choices," Economics of Education Working Paper Series 0251, University of Zurich, Department of Business Administration (IBW).
    • Handle: RePEc:iso:educat:0251
    as

    Download full text from publisher

    File URL: http://repec.business.uzh.ch/RePEc/iso/leadinghouse/0251_lhwpaper.pdf
    Download Restriction: no
    ---><---

    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. Menapace, Luisa & Raffaelli, Roberta, 2020. "Unraveling hypothetical bias in discrete choice experiments," Journal of Economic Behavior & Organization, Elsevier, vol. 176(C), pages 416-430.
    3. Daron Acemoglu & Pascual Restrepo, 2019. "Automation and New Tasks: How Technology Displaces and Reinstates Labor," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 3-30, Spring.
    4. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The Skill Content of Recent Technological Change: An Empirical Exploration," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(4), pages 1279-1333.
    5. Maarten Goos & Alan Manning, 2007. "Lousy and Lovely Jobs: The Rising Polarization of Work in Britain," The Review of Economics and Statistics, MIT Press, vol. 89(1), pages 118-133, February.
    6. Alexandre Mas & Amanda Pallais, 2017. "Valuing Alternative Work Arrangements," American Economic Review, American Economic Association, vol. 107(12), pages 3722-3759, December.
    7. Fouarge, Didier & Fregin, Marie-Christine & Janssen, Simon & Levels, Mark & Montizaan, Raymond & Özgül, Pelin & Rounding, Nicholas & Stops, Michael, 2025. "How AI-Augmented Training Improves Worker Productivity," IZA Discussion Papers 18224, IZA Network @ LISER.
    8. David Autor & Claudia Goldin & Lawrence F. Katz, 2020. "Extending the Race between Education and Technology," AEA Papers and Proceedings, American Economic Association, vol. 110, pages 347-351, May.
    9. Matthew Wiswall & Basit Zafar, 2018. "Preference for the Workplace, Investment in Human Capital, and Gender," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(1), pages 457-507.
    10. Arne Hole & Julie Kolstad, 2012. "Mixed logit estimation of willingness to pay distributions: a comparison of models in preference and WTP space using data from a health-related choice experiment," Empirical Economics, Springer, vol. 42(2), pages 445-469, April.
    11. Carvajal, Daniel & Franco, Catalina & Isaksson, Siri, 2024. "Will Artificial Intelligence Get in the Way of Achieving Gender Equality?," Discussion Paper Series in Economics 3/2024, Norwegian School of Economics, Department of Economics, revised 28 Apr 2025.
    12. Mauro Cazzaniga & Augustus Panton & Longji Li & Carlo Pizzinelli & Marina M. Tavares, 2025. "A Gender Lens on Labor Market Exposure to AI," AEA Papers and Proceedings, American Economic Association, vol. 115, pages 56-61, May.
    13. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    14. José Ignacio Conde-Ruiz & Juan José Ganuza Fernandez & Manuel García & Carlos Victoria Lanzón, 2024. "AI and Digital Technology: Gender Gaps in Higher Education," CESifo Economic Studies, CESifo Group, vol. 70(3), pages 244-270.
    15. Riccardo Scarpa & Mara Thiene & Francesco Marangon, 2008. "Using Flexible Taste Distributions to Value Collective Reputation for Environmentally Friendly Production Methods," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 56(2), pages 145-162, June.
    16. Ed Felten & Manav Raj & Robert Seamans, 2023. "How will Language Modelers like ChatGPT Affect Occupations and Industries?," Papers 2303.01157, arXiv.org, revised Mar 2023.
    17. Erik Brynjolfsson & Danielle Li & Lindsey Raymond, 2025. "Generative AI at Work," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 140(2), pages 889-942.
    18. Revelt, David & Train, Kenneth, 2000. "Customer-Specific Taste Parameters and Mixed Logit: Households' Choice of Electricity Supplier," Department of Economics, Working Paper Series qt1900p96t, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    19. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74(2), pages 132-132.
    20. Antonio Filippin, 2022. "Gender differences in risk attitudes," World of Labour, LISER, pages 100-100, October.
    21. John Loomis, 2011. "What'S To Know About Hypothetical Bias In Stated Preference Valuation Studies?," Journal of Economic Surveys, Wiley Blackwell, vol. 25(2), pages 363-370, April.
    22. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue nov.
    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. Gschwendt, Christian & Viarengo, Martina & Zollner, Thea S., 2026. "Generative AI and Career Choices," IZA Discussion Papers 18456, IZA Network @ LISER.
    2. Cattaneo, Maria A. & Gschwendt, Christian & Wolter, Stefan C., 2025. "How scary is the risk of automation? Evidence from a large-scale survey experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 235(C).
    3. Akshay Vij & Lynette Washington & Sally Weller & Jacob Irving & Ilke Onur, 2024. "Labour Market Preferences of Retrenched Australian Auto Industry Workers for Job Quality and Meaningful Work," The Economic Record, The Economic Society of Australia, vol. 100(329), pages 209-233, June.
    4. Goller, Daniel & Gschwendt, Christian & Wolter, Stefan C., 2025. "This time it’s different – Generative artificial intelligence and occupational choice," Labour Economics, Elsevier, vol. 95(C).
    5. Maria A. Cattaneo & Christian Gschwendt & Stefan C. Wolter, 2024. "How Scary is the Risk of Automation? Evidence from a Large Survey Experiment," Economics of Education Working Paper Series 0213, University of Zurich, Department of Business Administration (IBW).
    6. Martin Lábaj & Tomáš Oleš & Gabriel Procházka, 2025. "Impact of robots and artificial intelligence on labor and skill demand: evidence from the UK," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 15(4), pages 953-1001, December.
    7. Kiran Tomlinson & Sonia Jaffe & Will Wang & Scott Counts & Siddharth Suri, 2025. "Working with AI: Measuring the Applicability of Generative AI to Occupations," Papers 2507.07935, arXiv.org, revised Dec 2025.
    8. Lipowski, Cäcilia & Salomons, Anna & Zierahn-Weilage, Ulrich, 2024. "Expertise at work: New technologies, new skills, and worker impacts," ZEW Discussion Papers 24-044, ZEW - Leibniz Centre for European Economic Research.
    9. David Autor & Caroline Chin & Anna Salomons & Bryan Seegmiller, 2024. "New Frontiers: The Origins and Content of New Work, 1940–2018," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 139(3), pages 1399-1465.
    10. repec:ces:ceswps:_10955 is not listed on IDEAS
    11. Peeyush Agarwal & Harsh Agarwal & Akshat Rana, 2025. "What Work is AI Actually Doing? Uncovering the Drivers of Generative AI Adoption," Papers 2510.23669, arXiv.org, revised Oct 2025.
    12. Zhao, Dan & Tang, Ningyu & Hai, Shenyang & Zhao, Lijing, 2025. "Dual effects of AI-enabled job non-routinization on creativity: The moderating role of tacit knowledge awareness," Journal of Business Research, Elsevier, vol. 198(C).
    13. Sebastian, Raquel & Salas-Rojo, Pedro & C. Palomino, Juan & G. Rodríguez, Juan, 2026. "New technologies and the rise of wage inequality," INET Oxford Working Papers 2026-04, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    14. Ekaterina Prytkova & Fabien Petit & Deyu Li & Sugat Chaturvedi & Tommaso Ciarli, 2024. "The Employment Impact of Emerging Digital Technologies," CEPEO Working Paper Series 24-01, UCL Centre for Education Policy and Equalising Opportunities, revised Feb 2024.
    15. Bhalotra, Sonia & Fernandez, Manuel & Wang, Fan, 2022. "The Distribution of the Gender Wage Gap: An Equilibrium Model," CEPR Discussion Papers 17253, Centre for Economic Policy Research.
    16. Flavio Calvino & Chiara Criscuolo & Luca Fontanelli & Lionel Nesta & Elena Verdolini, 2024. "The role of human capital for AI adoption: Evidence from French firms," CEP Discussion Papers dp2055, Centre for Economic Performance, LSE.
    17. Fontanelli, Luca & Calvino, Flavio & Criscuolo, Chiara & Nesta, Lionel & Verdolini, Elena, 2025. "Human after all: Occupations at the core of AI adoption," Labour Economics, Elsevier, vol. 95(C).
    18. Engberg, Erik & Koch, Michael & Lodefalk, Magnus & Schroeder, Sarah, 2025. "Artificial intelligence, tasks, skills, and wages: Worker-level evidence from Germany," Research Policy, Elsevier, vol. 54(8).
    19. Kudoh, Noritaka & Miyamoto, Hiroaki, 2025. "Robots, AI, and unemployment," Journal of Economic Dynamics and Control, Elsevier, vol. 174(C).
    20. Hakan Yilmazkuday, 2025. "Artificial intelligence and labor markets: evidence from google trends," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 49(4), pages 1078-1093, December.
    21. Caselli, Mauro & Fracasso, Andrea & Scicchitano, Sergio & Traverso, Silvio & Tundis, Enrico, 2025. "What workers and robots do: An activity-based analysis of the impact of robotization on changes in local employment," Research Policy, Elsevier, vol. 54(1).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • 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:iso:educat:0251. 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: Sara Brunner (email available below). General contact details of provider: https://edirc.repec.org/data/isuzhch.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.