Five US Tech Giants Accumulate $1.65 Trillion in Hidden AI Debt

Five of the largest US technology companies have accumulated approximately $1.65 trillion in hidden, off-balance-sheet debt to fund the rapid buildout of artificial intelligence infrastructure. This represents an eightfold increase since 2022, signaling a massive shift in how hyperscalers are financing the AI race.

According to a study by Nikkei, this "hidden debt" consists primarily of data center leases and GPU supply contracts that do not appear as traditional loans on balance sheets. The scale of this leverage is most evident at Meta, where off-balance-sheet liabilities are estimated at $420 billion—nearly triple the company's reported transparent debt of roughly $140 billion. To sustain this momentum, the group—comprising Alphabet, Amazon, Meta, Microsoft, and Oracle—issued approximately $121 billion in bonds in 2025, a staggering jump from the 2020-2024 annual average of $28 billion.

The Capital Crunch

This borrowing binge comes as hyperscalers face an unprecedented capital expenditure cycle. Estimated AI spending has climbed to $725 billion in 2026, a surge that has severely squeezed free cash flow for these giants, with some reports indicating it is approaching zero.

To avoid saturating the US market and to find more favorable rates, these firms are diversifying their funding by tapping into European, Japanese, and Swiss markets. John Servidea, JPMorgan co-head of global investment grade financing, noted that raising debt in foreign currencies allows companies to leave longer intervals between tapping the US market and build "some scarcity value."

A Systemic Risk

Industry analysts warn that this financial strategy creates a dangerous "duration mismatch." While the debt used to fund these projects often carries terms of five to 20 years, the underlying AI hardware, such as GPUs, typically becomes obsolete every 18 to 36 months.

If the expected returns on AI investments fail to materialize quickly, these companies could face a "refinancing cliff," where they are left paying off long-term debt for assets that no longer provide competitive value. Neil Shearing, Group Chief Economist at Capital Economics, warned that "excess leverage has a habit of turning sectoral bubbles into systemic problems, with spillovers to the real economy."

What to Watch

Market observers are now monitoring whether these firms can transition from the infrastructure-building phase to a monetization phase fast enough to service their growing liabilities. The primary concern remains whether a market correction in AI utility would transform this concentrated corporate leverage into a broader financial crisis.