AI Data-Center Debt Moves Off Balance Sheets as Spending Could Reach $5.3T

Special-purpose entities can keep much of a project’s construction debt outside a technology customer’s financial statements, while disclosures, physical assets and demand remain central to the case for the buildout.

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AI Data-Center Debt Moves Off Balance Sheets as Spending Could Reach $5.3T
AI Data-Center Debt Moves Off Balance Sheets as Spending Could Reach $5.3T

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More than 120 billion dollars in AI data-center spending had been moved off technology companies’ balance sheets by December 2025, according to the Financial Times. The structure is straightforward: a separate project company raises the money and builds the facility, while a technology customer contracts for exclusive, full use once it is finished. Much of the construction debt may remain outside the customer’s financial statements. Gene Marks says Meta, Oracle, xAI, and CoreWeave are among the companies using structures that may keep some long-term obligations off their books. The scale is significant. Goldman Sachs estimates that hyperscalers could spend 5.3 trillion dollars on AI and data centers through 2030. That is a projection, not a committed spending total, but it shows how much capital could flow through private lenders and facility owners. The arrangement does not erase the underlying risk. Projects can underperform, lenders can lose money, and buildings, electrical systems, and computing equipment can lose value. The market backdrop is tight: CBRE says North American data-center capacity rose 36 percent in the prior year, while vacancy fell to a record-low 1.4 percent. Microsoft estimates that 17.8 percent of the world’s working-age population uses generative AI. The key question is whether that demand stays strong enough—and whether disclosures accurately capture the obligations created outside the technology customer’s balance sheet.

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AI infrastructure financing is increasingly being routed through separate project entities, allowing hyperscalers and model companies to secure exclusive data-center capacity while potentially keeping construction debt off their balance sheets. More than $120 billion had reportedly been shifted this way by December 2025, against Goldman Sachs’ estimated $5.3 trillion AI and data-center investment through 2030. The...

  1. 01

    Goldman Sachs’ $5.3 trillion projection is an estimate, not a committed spending total.

  2. 02

    CBRE reported North American capacity rose 36% while vacancy reached a record-low 1.4%.

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    Project entities can fund construction while customers retain exclusive use of completed facilities.

Off-balance-sheet financing can make AI data-center borrowing less visible on a technology customer’s books without making the underlying project disappear. The Financial Times reported in December 2025 that more than $120 billion of AI data-center spending had been shifted off balance sheets; Goldman Sachs estimates hyperscalers could spend $5.3 trillion on AI and data centers through 2030.

Capacity is contracted while financing sits elsewhere

The structure described by Gene Marks puts a separate entity in charge of raising capital and building the data center. The technology company contracts for exclusive, full use after completion, while most construction debt may remain outside that customer’s balance sheet. Marks identifies Meta, Oracle, xAI and CoreWeave among companies raising billions through structures that may keep some long-term obligations off their books.

That approach puts private markets in a larger role in the buildout, according to Goldman Sachs. Its $5.3 trillion figure is an estimate rather than a committed spending total, but it underscores the scale of capital being contemplated through 2030.

Physical infrastructure is not a fraud defense

Marks argues that the Enron comparison goes too far, while still calling for scrutiny of disclosures and consolidation. His case is that current disclosure requirements are significant, scrutiny is intense, and the financed assets are land, buildings, electrical infrastructure and computing equipment. Unlike a biotechnology program that fails clinical testing, a data center can disappoint financially without disappearing.

The risks that remain at the project level

  • Some individual data-center investments may fail.
  • Lenders may lose money on projects they finance.
  • Facilities may be worth less than their owners paid for them.

Tight capacity supports the case, not every investment

CBRE said North American data-center capacity increased 36% in the prior year while vacancy fell to a record 1.4%. It also said demand was outpacing supply in nearly every major market. Those figures establish a tight market, even as they do not assure returns for each facility now being financed.

Microsoft estimates that 17.8% of the world’s working-age population currently uses generative AI. Marks sees that estimate as evidence that adoption may still be early. The live question is whether that demand remains strong enough to support facilities whose owners and lenders bear the risk of weaker project economics.

Sources

  1. theguardian.comAn AI ‘debt bomb’ crisis? No. This isn’t Enron 2.0 | Gene Marks

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