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Gen-AI: Artificial Intelligence and the Future of Work

Author

Listed:
  • Mauro Cazzaniga
  • Ms. Florence Jaumotte
  • Longji Li
  • Mr. Giovanni Melina
  • Augustus J Panton
  • Carlo Pizzinelli
  • Emma J Rockall
  • Ms. Marina Mendes Tavares

Abstract

Artificial Intelligence (AI) has the potential to reshape the global economy, especially in the realm of labor markets. Advanced economies will experience the benefits and pitfalls of AI sooner than emerging market and developing economies, largely due to their employment structure focused on cognitive-intensive roles. There are some consistent patterns concerning AI exposure, with women and college-educated individuals more exposed but also better poised to reap AI benefits, and older workers potentially less able to adapt to the new technology. Labor income inequality may increase if the complementarity between AI and high-income workers is strong, while capital returns will increase wealth inequality. However, if productivity gains are sufficiently large, income levels could surge for most workers. In this evolving landscape, advanced economies and more developed emerging markets need to focus on upgrading regulatory frameworks and supporting labor reallocation, while safeguarding those adversely affected. Emerging market and developing economies should prioritize developing digital infrastructure and digital skills

Suggested Citation

  • Mauro Cazzaniga & Ms. Florence Jaumotte & Longji Li & Mr. Giovanni Melina & Augustus J Panton & Carlo Pizzinelli & Emma J Rockall & Ms. Marina Mendes Tavares, 2024. "Gen-AI: Artificial Intelligence and the Future of Work," IMF Staff Discussion Notes 2024/001, International Monetary Fund.
    • Handle: RePEc:imf:imfsdn:2024/001
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    Citations

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    Cited by:

    1. Raphael Auer & David Köpfer & Josef Sveda, 2024. "The rise of generative AI: modelling exposure, substitution and inequality effects on the US labour market," BIS Working Papers 1207, Bank for International Settlements.
    2. Antonio Dalla Zuanna & Davide Dottori & Elena Gentili & Salvatore Lattanzio, 2024. "An assessment of occupational exposure to artificial intelligence in Italy," Questioni di Economia e Finanza (Occasional Papers) 878, Bank of Italy, Economic Research and International Relations Area.
    3. Kudoh, Noritaka & Miyamoto, Hiroaki, 2025. "Robots, AI, and unemployment," Journal of Economic Dynamics and Control, Elsevier, vol. 174(C).
    4. Wang, Shaofeng & Zhang, Hao, 2025. "Artificial intelligence digital employees and sustainable innovation in online retail: The mediating role of ambidextrous green innovation and the moderating role of ethical anxiety," Journal of Retailing and Consumer Services, Elsevier, vol. 84(C).
    5. Aldasoro, Iñaki & Armantier, Olivier & Doerr, Sebastian & Gambacorta, Leonardo & Oliviero, Tommaso, 2024. "The gen AI gender gap," Economics Letters, Elsevier, vol. 241(C).
    6. Schrape, Jan-Felix, 2025. "Artificial intelligence and social action: A techno-sociological contextualization," Research Contributions to Organizational Sociology and Innovation Studies, SOI Discussion Papers 2025-03, University of Stuttgart, Institute for Social Sciences, Department of Organizational Sociology and Innovation Studies.
    7. David Loschiavo & Mirko Moscatelli, 2025. "Adoption and expected impact of Generative AI: evidence from Italian households," Questioni di Economia e Finanza (Occasional Papers) 929, Bank of Italy, Economic Research and International Relations Area.
    8. Demombynes, Gabriel & Langbein, Jorg Gero & Weber, Michael, 2025. "The Exposure of Workers to Artificial Intelligence in Low- and Middle-Income Countries," Policy Research Working Paper Series 11057, The World Bank.
    9. Yusuke Aoki & Joon Suk Park & Yuya Takada & Koji Takahashi, 2025. "Expecting job replacement by GenAI: effects on workers' economic outlook and behavior," BIS Working Papers 1269, Bank for International Settlements.
    10. Alexandrov, Georgii A., 2025. "When does artificial intelligence replace process-based models in ecological modelling?," Ecological Modelling, Elsevier, vol. 499(C).

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