Bond Investors Push Back As AI Debt Heads Toward $570 Billion

The bond market has been flashing warning signs for months, but few are willing to confront what this means for the future of Artificial Intelligence (AI). Companies continue to borrow heavily to finance their AI buildout, and a staggering $570 billion in global AI-related debt issuance is projected for 2026. This number is not a crisis, but rather a symptom of a larger issue – who ends up holding the risk of this massive investment.

The scale of this risk can be understood by examining the role of credit markets in financing AI. According to Morgan Stanley, about $236 billion had been priced by May 31, a fourfold increase from the previous year. This is not just a story about hyperscalers; it’s a broad wave of debt issuance that involves other AI-linked issuers and financing structures.

The bond market is signaling that companies may need to pay more for this capital, but investors are still willing to take on the risk. However, the narrative surrounding AI-related debt often gets muddled by a $1.5 trillion figure touted as the amount hyperscalers must take on. This number is actually a funding gap, not a debt forecast, and it can be filled with various types of financing.

Morgan Stanley’s analysis suggests that Big Tech companies have enough cash flow to cover their AI spending, but they’re choosing to spread the cost across credit markets instead. This decision reduces the risk for these companies while spreading the risk to investors. The giants are borrowing when they don’t have to because it preserves options and maintains financial flexibility.

The public bond market is not flashing red lights yet; spreads remain near cycle lows. However, more of this financing is expected to move outside public markets and into private credit vehicles. Morgan Stanley projects an approximately $800 billion opportunity in data-center financing through 2028, which can sit in off-balance-sheet vehicles called shadow borrowing.

This structure allows companies to hide debt from their balance sheets, making losses harder to spot if returns fall short. Executives should be asking a different question – who finances the wait and who gets hurt if returns arrive late or fall short? Companies should map these dependencies and understand that most of the exposure is indirect.

It may surface through higher prices, capacity limits, or counterparty risk even if you never buy an AI-related security. The bond market’s softening demand is not a crisis; it’s a signal that investors are demanding wider spreads to absorb additional supply. Order books covered nearly five times the bonds offered in February, but less than two times in July.

This means the price of patience is rising, and more of the risk now sits outside the balance sheets everyone watches. The AI buildout may be driven by optimism about future returns, but it’s also creating a complex web of debt dependencies that few want to acknowledge. As we move forward, it’s essential to understand who’s financing this wait and who will get hurt if the returns don’t materialize as expected.

The bond market is sending a warning signal – one that should not be ignored.