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AI and the Fed

Author

Listed:
  • Sophia Kazinnik
  • Erik Brynjolfsson

Abstract

This paper examines how central banks can strategically integrate artificial intelligence (AI) to enhance their operations. Using a dual-framework approach, we demonstrate how AI can transform both strategic decision-making and daily operations within central banks, taking the Federal Reserve System (FRS) as a representative example. We first consider a top-down view, showing how AI can modernize key central banking functions. We then adopt a bottom-up approach focusing on the impact of generative AI on specific tasks and occupations within the Federal Reserve and find a significant potential for workforce augmentation and efficiency gains. We also address critical challenges associated with AI adoption, such as the need to upgrade data infrastructure and manage workforce transitions.

Suggested Citation

  • Sophia Kazinnik & Erik Brynjolfsson, 2025. "AI and the Fed," NBER Working Papers 33998, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:33998
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    More about this item

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • G4 - Financial Economics - - Behavioral Finance

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