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AI and the future of work for economists: rethinking economics education

Author

Listed:
  • Matthias Oschinski
  • Christian Spielmann
  • Sonali Subbu-Rathinam

Abstract

Artificial Intelligence (AI) is transforming labor markets, including the professions pursued by economics graduates. This paper investigates the evolving impacts of AI—particularly generative AI—on occupations commonly entered by U.S. economics graduates and examines the implications for economics education at the university level. Using Lightcast data on job profiles and postings from 2015 to 2023, we identify how occupational patterns and skill profiles for economics graduates have changed and analyze the likely impact of AI on the economists’ job market. Economics graduates enter roles with higher-than-average AI exposure and varying degrees of task complementarity, suggesting that AI is likely to have substantive impacts on these jobs, with some effects already evident. We argue that university curricula must adapt to these changes to better prepare graduates for the AI-augmented workplace.

Suggested Citation

  • Matthias Oschinski & Christian Spielmann & Sonali Subbu-Rathinam, 2025. "AI and the future of work for economists: rethinking economics education," Bristol Economics Discussion Papers 25/788, School of Economics, University of Bristol, UK.
  • Handle: RePEc:bri:uobdis:25/788
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    References listed on IDEAS

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    1. Nicholas Crafts, 2021. "Artificial intelligence as a general-purpose technology: an historical perspective," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 37(3), pages 521-536.
    2. 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.
    3. David H. Autor & David Dorn, 2013. "The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market," American Economic Review, American Economic Association, vol. 103(5), pages 1553-1597, August.
    4. 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.
    5. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation and Work," Boston University - Department of Economics - Working Papers Series dp-298, Boston University - Department of Economics.
    6. Carlo Pizzinelli & Augustus J Panton & Ms. Marina Mendes Tavares & Mauro Cazzaniga & Longji Li, 2023. "Labor Market Exposure to AI: Cross-country Differences and Distributional Implications," IMF Working Papers 2023/216, International Monetary Fund.
    7. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    8. Edward Felten & Manav Raj & Robert Seamans, 2021. "Occupational, industry, and geographic exposure to artificial intelligence: A novel dataset and its potential uses," Strategic Management Journal, Wiley Blackwell, vol. 42(12), pages 2195-2217, December.
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