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Who is afraid of AI? Who should be?

Author

Listed:
  • Engberg, Erik
  • Görg, Holger
  • Hellsten, Mark
  • Javed, Farrukh
  • Lodefalk, Magnus
  • Längkvist, Martin
  • Monteiro, Natália Pimenta
  • Nordås, Hildegunn Kyvik
  • Pulito, Giuseppe
  • Schroeder, Sarah
  • Tang, Aili

Abstract

• Occupations that are highly cognitive, non-physical, and low in social interaction - typically higher-skill white-collar roles such as data analysts, software developers, and translators - turn out to be highly AI-exposed • Occupations requiring manual dexterity or intensive interpersonal contact - such as construction labourers or nursing aides - remain among the least exposed to current AI technologies • Aggregate occupational exposure to AI has risen markedly since 2010, with especially rapid gains in the late 2010s and early 2020s • Our baseline estimates show no detectable effect of AI exposure on total firm employment, while it is associated with clear skill upgrading

Suggested Citation

  • Engberg, Erik & Görg, Holger & Hellsten, Mark & Javed, Farrukh & Lodefalk, Magnus & Längkvist, Martin & Monteiro, Natália Pimenta & Nordås, Hildegunn Kyvik & Pulito, Giuseppe & Schroeder, Sarah & Tang, 2026. "Who is afraid of AI? Who should be?," Kiel Policy Briefs 198, Kiel Institute for the World Economy.
    • Handle: RePEc:zbw:ifwkpb:336753
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    References listed on IDEAS

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    1. Michael J. Handel, 2016. "The O*NET content model: strengths and limitations [Stärken und Grenzen des O*NET-Models]," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 49(2), pages 157-176, October.
    2. David J. Deming & Christopher Ong & Lawrence H. Summers, 2025. "Technological Disruption in the Labor Market," NBER Working Papers 33323, National Bureau of Economic Research, Inc.
    3. Handel, Michael J., 2016. "The O-NET content model: strengths and limitations," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 49(2), pages 157-176.
    4. Edward W. Felten & Manav Raj & Robert Seamans, 2018. "A Method to Link Advances in Artificial Intelligence to Occupational Abilities," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 54-57, May.
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    Keywords

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    JEL classification:

    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • N34 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy - - - Europe: 1913-
    • 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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