Hidden AI-related debt surges to $1.65 trillion.

The massive financial demands of the artificial intelligence boom are driving tech giants into unprecedented levels of borrowing, both visible and hidden. According to S&P Global, hyperscalers and related firms like Nvidia have issued $225 billion in bonds so far in 2026, marking a 973.7 percent surge through midyear. These companies are currently on track to issue $400 billion in bonds for the full year. However, this visible debt is only part of the story, as market fatigue begins to set in and investors demand higher premiums compared to risk-free bonds, especially with a federal budget deficit approaching nearly $2 trillion.

Beyond public bond markets, a parallel financial expansion is occurring off the books. A study by Nikkei reveals that hidden debt at major U.S. tech firms has grown eightfold over four years, reaching $1.65 trillion. This off-balance-sheet liability now exceeds the $1.35 trillion in official debt recorded on their balance sheets. These hidden obligations typically stem from long-term purchase agreements for graphics processing units and servers, alongside lease contracts with data center operators. Moody's similarly flagged these off-balance-sheet arrangements, valuing them at $1.2 trillion, with more than $820 billion tied directly to data centers currently under construction.

For AI practitioners, developers, and enterprise customers, this massive financial transition from asset-light software models to asset-heavy infrastructure models carries significant long-term implications. While Moody's notes that hyperscalers like Amazon maintain robust investment-grade ratings, the sheer volume of debt and rising borrowing costs could eventually pressure cloud providers to adjust their pricing structures. As the "rivers of capital" described by RSM economist Joseph Brusuelas begin to flow less freely, developers may face higher API costs, tighter compute allocations, or shifting lease terms for high-performance hardware. Understanding that the underlying physical infrastructure of AI is being built on a trillion-dollar mountain of debt is crucial for teams planning multi-year cloud budgets and architecture strategies.