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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. Aldasoro, Iñaki & Armantier, Olivier & Doerr, Sebastian & Gambacorta, Leonardo & Oliviero, Tommaso, 2024. "The gen AI gender gap," Economics Letters, Elsevier, vol. 241(C).

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