U.S. Tech Giants' Hidden AI Debt Soars to $1.65 Trillion, Eightfold Increase in Four Years Raises Market Concerns

On July 24, the hidden debt incurred by five major U.S. tech giants due to the expansion of AI infrastructure has reached $1.65 trillion, an approximately eightfold increase from four years ago, surpassing the total on-balance-sheet liabilities of $1.35 trillion during the same period.

As AI competition intensifies, tech giants are making massive investments in data centers, GPU, and server procurement, locking in computing resources through long-term leasing agreements and equipment procurement contracts. Due to U.S. GAAP accounting standards, certain undelivered equipment purchases and unused data center leases do not need to be immediately recorded on the balance sheet; these future payment obligations are typically disclosed only in the notes to the financial statements.

Data shows that the AI capital expenditures of the five tech companies continue to expand. Among them, capital expenditures for fiscal year 2025 are expected to reach $85 billion; capital expenditures for the first quarter of fiscal year 2026 are projected to be $34.9 billion; plans for 2026 include an investment of about $200 billion, primarily for AWS data centers and AI chips; capital expenditures for 2025 are expected to be between $60 billion and $65 billion; driven by cloud service orders, capital expenditures for fiscal year 2027 are expected to rise to between $90 billion and $95 billion.

Data indicates that signed but not yet recorded data center leasing commitments amount to approximately $662 billion, accounting for 113% of the adjusted debt of the five companies. As leasing agreements gradually take effect, over $500 billion of related debt may transition to formal financial statements.

Analysts warn that if the revenue growth from AI business does not match the rapid expansion of capital investment, the enormous long-term commitments may weaken the cash flow flexibility of the companies.

Additionally, the expansion model of the AI industry has also raised risks of "shadow lending" and circular investments. Some tech companies are financing AI infrastructure through bond financing, equity financing, and off-balance-sheet contracts, while the capital cycle formed between these tech giants is also questioned by the market for potentially amplifying industry prosperity expectations and masking the risks of insufficient real demand.

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