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The macroeconomic implications of the Gen-AI economy

Author

Listed:
  • Pablo Guerron-Quintana

    (Boston College)

  • Tomoaki Mikami

    (Boston College)

  • Jaromir Nosal

    (Boston College)

Abstract

We study the potential impact of the generative artificial intelligence (Gen-AI) revolution on the US economy through the lens of a multi-sector model in which we explicitly model the role of Gen-AI services in customer base management. In our model with carefully calibrated input-output linkages and the size of the Gen-AI sector, we find large spillovers of the Gen-AI productivity gains into the overall economy. A 10% increase in productivity in the Gen-AI sector over a 10 year horizon implies a 6% increase in aggregate GDP, despite the AI sector representing only 14% of the overall economy. That shock also implies a significant reallocation of labor away from the AI sector and into non-AI sectors. We decompose these effects into parts coming from the input-output structure and customer base management and find that they each contribute equally to the rise in GDP. In the absence of either channels, real GDP essentially does not respond to the increase in productivity in the AI sector.

Suggested Citation

  • Pablo Guerron-Quintana & Tomoaki Mikami & Jaromir Nosal, 2024. "The macroeconomic implications of the Gen-AI economy," Boston College Working Papers in Economics 1080, Boston College Department of Economics.
    • Handle: RePEc:boc:bocoec:1080
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    References listed on IDEAS

    as
    1. Leena Rudanko, 2025. "Price Setting with Customer Capital: Sales, Teasers, and Rigidity," Journal of Political Economy Macroeconomics, University of Chicago Press, vol. 3(2), pages 241-268.
    2. Roldan-Blanco, Pau & Gilbukh, Sonia, 2021. "Firm dynamics and pricing under customer capital accumulation," Journal of Monetary Economics, Elsevier, vol. 118(C), pages 99-119.
    3. 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.
    4. Kyogo Kanazawa & Daiji Kawaguchi & Hitoshi Shigeoka & Yasutora Watanabe, 2026. "AI, Skill, and Productivity: The Case of Taxi Drivers," Management Science, INFORMS, vol. 72(2), pages 1376-1388, February.
    5. Babina, Tania & Fedyk, Anastassia & He, Alex & Hodson, James, 2024. "Artificial intelligence, firm growth, and product innovation," Journal of Financial Economics, Elsevier, vol. 151(C).
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    Keywords

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    JEL classification:

    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights

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