Primary source BusinessArticle·24 September 2026·4 min read

$10.3 Trillion for AI: The Data Center Bill Flying Under the Radar

A Columbia economist sizes up the AI buildout beyond rail and highways—and worries most about how it's being financed.

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$10.3 Trillion for AI: The Data Center Bill Flying Under the Radar

Source : Stijn Van Nieuwerburgh (Brookings, BPEA) · BrookingsView original ↗

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In brief

According to a paper presented at the Brookings Papers on Economic Activity, US investment in AI infrastructure could reach $10.3 trillion between 2025 and 2032, or 3.63% of GDP per year. Stijn Van Nieuwerburgh (Columbia) observes that this financing is shifting from the balance sheets of large companies toward opaque off-balance-sheet structures: joint ventures, private credit, securitization, SPVs. Without yet calling it systemic risk, he calls for more measurement and transparency while the sector's structure remains malleable.

🍺 Bar-stool version

We're talking $10.3 trillion in data centers, chips, and power plants by 2032—more, relative to the economy, than America's canals, railroads, electrification, and highways combined. So far, nothing abnormal; humanity loves building gigantic things. The problem is that the debt no longer sits in the accounts of tech giants but in off-balance-sheet arrangements with charming names, tucked away like boxes in a cousin's garage. The day things wobble, nobody will know exactly who owes what to whom, and in finance, that's rarely the start of a story that ends well.

Key takeaways

1
The paper projects $10.3 trillion in AI infrastructure investment in the US between 2025 and 2032: data center buildings, power systems, grid, chips, and equipment.
2
This represents an average of 3.63% of US GDP each year over the period.
3
Relative to the size of the economy, this buildout would exceed the great historical booms: canals, railroads, electrification, highways, and telecommunications.
4
Financing is migrating from the transparent balance sheets of large companies toward off-balance-sheet structures: joint ventures, private credit, securitization, SPVs, lease commitments, loan guarantees.
5
These arrangements depend on cash flows and asset values, exposed to uncertain AI demand, rapid technological obsolescence, access to energy and hardware, and the solidity of a small number of tenants.
6
The author considers it premature to speak of systemic risk comparable to past credit booms, but fears correlated exposures could remain invisible until a downturn.
7
His main recommendation: improve measurement and transparency now, while the sector's capital structure is still taking shape.

A bigger project than the railroads

The figure is striking: $10.3 trillion invested between 2025 and 2032 in data centers, power supply, networks, and specialized chips.

The debt changes address

The heart of the paper isn't the amount, but the financial plumbing.

Not yet a bubble, but a blind spot

The author refrains from crying crisis.

A paper in a series on AI

This work is one of three papers presented on September 25 at the BPEA fall conference dedicated to the risks and promises of AI, alongside "Why is AI so contentious" and "The vanishing advantage of specialization."

Why it matters

The debate over a potential AI bubble often focuses on stock valuations or the capex announced by hyperscalers.

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#data centers #financing #debt #economics #infrastructure #ai

Original source

Financing the AI buildout

Stijn Van Nieuwerburgh (Brookings, BPEA)

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