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Can AI restore fiscal sustainability in the US?

Accounting for an AI-driven productivity shock

Ben Harris,
Ben Harris
Ben Harris Vice President and Director - Economic Studies, The Bruce and Virginia MacLaury Chair
Neil R. Mehrotra, and
Neil R. Mehrotra Assistant Vice President and Policy Advisor - Federal Reserve Bank of Minneapolis
William Overcash

July 1, 2026


  • AI-driven economic growth can meaningfully shrink fiscal deficits, but is unlikely to close the gap even in more optimistic scenarios. A once-in-a-generation productivity shock could cut deficits by about 5 percentage points of GDP by 2036, but several factors specific to an AI shock could claw back more than half of those gains.
  • Five offsetting forces may blunt the benefit: Longer lifespans could raise old-age entitlement spending, displaced workers might strain income-support programs, income shifts from labor to capital might lower average tax rates, higher interest rates could potentially raise debt service costs, and an AI arms race could possibly lift defense spending.
  • GDP growth assumptions matter most. Of all variables, the GDP growth rate has by far the largest effect on projected deficits, making AI’s macroeconomic impact the key uncertainty.
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Editor's note:

This is a Brookings Economic Studies Program working paper.

Introduction

This paper examines whether AI-driven productivity growth can resolve the United States’ unsustainable fiscal trajectory, projected by CBO to push public debt to 175% of GDP by 2056. Building on historical evidence, the authors construct a fiscal and macroeconomic model identifying both conventional channels (higher GDP, elevated interest rates) and novel AI-specific channels (reduced mortality, shifting labor force participation, increased defense spending) through which an AI shock would affect the federal budget over a 10-year horizon. The model simulates four scenarios: a traditional, broad-based productivity shock; a labor-market-disrupting shock; a health-focused shock; and a composite scenario combining all three.

The authors find that a once-in-a-generation productivity shock could reduce annual deficits from roughly 6% to 2% of GDP. However, the idiosyncratic nature of an AI-driven shock might limit these gains through five channels: lower mortality expands the retirement-age population and entitlement spending; a shift from higher-taxed labor income to lower-taxed capital income narrows the tax base; reduced labor force participation increases income-support enrollment; higher interest rates raise debt-service costs; and a potential AI arms race accelerates defense spending. Together, these factors could recapture more than half the fiscal benefit of a conventional productivity shock, suggesting that while AI can materially improve the budget outlook, it is unlikely to fully resolve the nation’s fiscal imbalance on its own.

Download the full working paper

 

Authors

  • Acknowledgements and disclosures

    We thank Martin Baily, Marc Goldwein, Liam Marshall, Ryan Nunn, Mike O’Hanlon, and Sanjay Patnaik for helpful comments and suggestions. This working paper was made possible by support from Peterson G. Peterson Foundation. All errors are our own.

    Benjamin H. Harris and William Overcash are with the Brookings Institution, and Neil Mehrotra is with the Federal Reserve Bank of Minneapolis. Their opinions are their own and do not necessarily represent the views of the Federal Reserve Bank of Minneapolis, the Federal Reserve System, or the Brookings Institution.

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