The paper summarized here is part of the fall 2026 edition of the Brookings Papers on Economic Activity, the leading conference series and journal in economics for timely, cutting-edge research about real-world policy issues. Research findings are presented in a clear and accessible style to maximize their impact on economic understanding and policymaking. The editors are Brookings Nonresident Senior Fellows Janice Eberly and Jón Steinsson.
See the fall 2026 BPEA event page to watch paper presentations and read summaries of all the papers from this edition. Submit a proposal to present at a future BPEA conference here.
Three papers to be presented on September 25 at the Brookings Papers on Economic Activity (BPEA) fall conference examine potential risks and rewards of the boom in artificial intelligence (AI): Why is AI so contentious, The vanishing advantage of specialization, and Financing the AI buildout.
Financing the AI buildout projects that AI investment in data center buildings, power systems, networking infrastructure, and specialized chips and other equipment will total an enormous $10.3 trillion from 2025 to 2032, or an average of 3.63% of U.S. gross domestic product per year.
“The projected buildout would be larger relative to the economy than the major U.S. canal, railroad, electrification, highway, and telecommunications investment booms,” writes the author, Stijn Van Nieuwerburgh of Columbia University.
The paper warns that the risks embodied in the AI investment race are migrating from transparent on-balance sheet financing by major corporations to opaque off-balance sheet financing through joint ventures, private credit, securitization, special-purpose vehicles, lease commitments, loan guarantees, and other structures.
These off-balance sheet arrangements then depend on AI companies’ cash flows and collateral values, which are subject to “uncertain AI demand, rapid technological change, timely access to power and hardware, and the continued credit quality of a small number of [data center] tenants,” Nieuwerburgh writes.
He writes that “it would be premature to conclude that AI infrastructure already poses systemic risk comparable to earlier credit booms” but notes that “off-balance sheet structures matter … because they may make correlated exposures hard to observe before a downturn.”
“The most important policy contribution at this stage may therefore be to improve measurement and transparency while the capital structure of the industry is still evolving,” he writes.
Author
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CITATION
Van Nieuwerburgh, Stijn. 2026. “Financing the AI Buildout.” BPEA Conference Draft, Fall.
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Acknowledgements and disclosures
David Skidmore authored the summary language for this paper.
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