The $489 Billion AI Debt Wave: Key Trends and Market Implications

Borrowers Are No Longer Just the Biggest Tech Companies

A defining shift in 2026 is how much the borrower base has widened. Goldman Sachs reports that about 40% of this year's AI-related debt supply has come from the largest hyperscalers — Amazon, Alphabet, Meta, Microsoft, and Oracle. The remaining ~60% is coming from a widening range of borrowers: AI infrastructure companies, data center operators, REITs, and even crypto miners pivoting to AI . This marks a significant departure from earlier concentration among a handful of megacap tech firms.

Amazon alone has issued $92 billion of bonds across currencies in 2026, the most among the hyperscalers, followed by Alphabet, Meta, and Oracle . But the new entrants are increasingly important.

The Galaxy Digital Junk-Bond Deal: A Bellwether for Risk

On July 22, 2026, Galaxy Digital announced its subsidiary Galaxy Helios Data Centers II LLC plans to offer $3.507 billion in senior secured notes due 2031 in a private offering . The proceeds will finance the Helios Data Center Campus in Dickens County, Texas — converting a former cryptocurrency mining site into an AI data center leased to CoreWeave under a 15-year agreement . Bloomberg characterized the deal as extending AI financing into the riskier corners of the U.S. credit market via a debut junk-bond sale . The bond is being marketed to investors at a yield of about 9%, with Morgan Stanley and Goldman Sachs serving as underwriters .

This deal is not an isolated case. An Applied Digital subsidiary raised $1.59 billion in the junk bond market in June 2026 to fund additional computing capacity for CoreWeave in North Dakota, with bonds issued at a yield of 7% — a notable decline from the 10% investors were seeking just a few months prior . Together, these transactions show AI financing moving decisively into higher-yield, higher-risk territory.

Is AI Debt Crowding Out U.S. Treasuries? An Active Debate

One of the most contested questions among strategists is whether the massive wave of AI borrowing is diminishing demand for U.S. Treasuries and pushing up long-term yields.

Apollo Chief Economist Torsten Slok asserts that the scale of AI borrowing is already diminishing demand for U.S. Treasuries and other fixed-income assets . Bloomberg's analysis reports that debt-fueled AI investment has helped push long-term borrowing costs to levels not seen since the financial crisis, with the 30-year Treasury yield hitting 11 straight sessions above 5% as of July 22, testing milestones not seen since 2007 .

However, other major asset managers push back. Columbia Threadneedle's Todd Czachor says he has not yet observed any signs of crowding out in the corporate bond market. "At least not yet," he remarked, noting that demand for corporate bonds has remained robust . PIMCO similarly says Treasury yields are currently driven by Fed policy bets, not AI borrowing, though it acknowledges AI debt could eventually lift term premia over time .

Reuters reports that the surge in AI-related investment contributed to the decline in May that drove 30-year Treasury yields to their highest point since 2007, alongside concerns about inflation and changing Fed policy expectations . The Dallas Federal Reserve has flagged three channels through which AI debt financing could impact duration supply and interest rates: direct issuance of long-term investment-grade corporate bonds, swapping of floating-rate loans from private credit investors, and possible crowding-out of financial issuers .

The bottom line: alarm is rising, yields are elevated, and AI supply is massive, but the evidence that AI debt is causing the Treasury selloff remains contested.

Off-Balance-Sheet Exposure: The Next Concern

The specific figure of $1.65 trillion in off-balance-sheet AI infrastructure obligations for the five largest tech companies could not be independently confirmed from the sources available. However, multiple sources confirm that hyperscalers carry substantial off-balance-sheet exposures through operating leases, power purchase agreements, and joint-venture structures for data centers, GPUs, and energy infrastructure.

The IESE article notes a "fast-growing pool of off-balance-sheet liabilities" in AI financing, which the Bank for International Settlements has labeled "shadow borrowing" . The BIS has flagged that private credit loans to AI companies have grown from near zero to over $200 billion outstanding, and extrapolating from projected AI investment growth, outstanding private credit to AI firms could reach around $300–600 billion by 2030 .

Analysts broadly agree that contingent AI infrastructure liabilities are large, opaque, and under-scrutinized by traditional credit metrics, even if the precise $1.65 trillion figure requires further sourcing.

Key Market Implications

• Borrower base broadening rapidly: Hyperscalers are still the largest single group at 40%, but the other 60% comes from specialty lenders, data center REITs, crypto-to-AI converts, and private credit funds.
• Credit market strain is visible: AI-related debt now accounts for roughly 30% of net new investment-grade supply in the U.S. dollar market . The 30-year Treasury yield's sustained breach above 5% is the steepest since 2007 .
• Junk-market risk is rising: The Galaxy Digital deal and Applied Digital's $1.59 billion junk offering show AI financing moving decisively into higher-yield, higher-risk territory.
• Off-balance-sheet exposure is the next concern: Even if the exact figure needs confirmation, analysts broadly agree that contingent AI infrastructure liabilities are large, opaque, and under-scrutinized by traditional credit metrics.