Technology • Finance

US Tech Giants' $1.65 Trillion Invisible Debt from AI Funding

The massive buildout of AI infrastructure has created a shadow debt system that regulators are only beginning to understand.
Five major US technology companies have accumulated approximately $1.65 trillion in off-balance-sheet liabilities through AI-driven data center financing, according to a Nikkei investigation. These "hidden debts" include lease obligations, equipment financing, and cloud computing prepurchase agreements that do not appear on traditional balance sheets.
The opaque financing structure is largely driven by the unprecedented capital demands of artificial intelligence. Training and deploying large language models requires massive clusters of GPUs and specialized hardware, with a single data center now costing $3 billion or more. Companies have turned to partnerships, joint ventures, and special-purpose vehicles to fund this expansion without triggering traditional debt covenants.
Financial analysts warn that these hidden liabilities could pose systemic risks if the AI boom slows. Unlike traditional corporate debt, many of these arrangements are structured as operating leases or service agreements that can be difficult to restructure. The situation has drawn comparisons to the off-balance-sheet vehicles that contributed to the 2008 financial crisis, though the scale and structure differ significantly.

The five companies — widely understood to be Alphabet, Amazon, Apple, Meta, and Microsoft — have collectively committed hundreds of billions to AI infrastructure over the past 18 months. Much of this spending flows through cloud computing divisions, where data center construction, GPU procurement, and energy contracts are packaged as "capital expenditures" that are then financed through third-party investment vehicles.

Morgan Stanley has emerged as the leading bank facilitating this AI debt boom, overtaking traditional rivals in the infrastructure finance space. The bank has structured dozens of complex financing deals that bundle AI hardware leases with long-term cloud service commitments, creating instruments that are difficult for investors and regulators to assess.

The scale of this invisible debt has caught the attention of financial regulators. The Securities and Exchange Commission has begun preliminary inquiries into how major tech companies disclose AI-related financial commitments. Investors are also pushing for greater transparency, arguing that shareholders cannot properly evaluate risk without understanding the full extent of these contingent liabilities.

Proponents argue that the financing structures are standard practice for capital-intensive industries and that the underlying assets — AI chips and data centers — retain significant value. However, the rapid pace of AI hardware obsolescence means that GPU clusters can lose value quickly, potentially leaving lenders exposed if the AI investment cycle turns.