The artificial intelligence boom is now reshaping credit markets as deeply as it has reshaped technology stocks. Banks are having to become more creative as borrowing tied to chips, cloud infrastructure and data centers surges to unprecedented levels. The reason is simple: the companies building the backbone of AI need so much money that traditional funding channels, especially the U.S. dollar bond market, are at risk of being overwhelmed.
The biggest borrowers are the major cloud and technology companies often called hyperscalers. Companies such as Amazon and Alphabet have issued $60 billion in bonds across multiple currencies over the past 12 months. Instead of relying only on the U.S. investment-grade market, they are increasingly selling debt in euros, sterling, yen, Canadian dollars and Swiss francs to tap a wider investor base and avoid saturating one market with enormous supply. These deals have already set records in several foreign-currency bond markets.
That shift reflects the scale of AI spending. BNP Paribas estimates that hyperscaler capital expenditures this year will reach about $725 billion, nearly double the level seen in mid-2025. Spending is rising faster than operating cash flow, which means even very profitable companies are turning to outside financing to keep up with the race to build AI capacity. In other words, AI is no longer being funded only out of tech-company cash piles; it is increasingly becoming a debt-financed buildout on a global scale.
Banks are also inventing new financing structures for AI-related borrowers beyond the mega-cap giants. For AI startups and data-center operators, some deals are now being structured around pre-arranged data-center leases, sometimes signed before construction even begins. These leases provide a clearer picture of future cash flow and make it easier to sell debt to investors. One recent example is an $810 million note sold by Stingray Compute, owned by Cipher Digital, backed by a lease to Amazon. Morgan Stanley said the deal was nine times oversubscribed, and roughly 15 similar lease-backed deals have been sold to high-yield investors since last year.
So far, demand has held up well despite the flood of issuance. AI-related debt in the U.S. is now close to 15% of total investment-grade bond issuance this year, according to Barclays. Morgan Stanley’s Teddy Hodgson said that total investment-grade issuance could top $2 trillion for the first time ever in 2026 if this pace continues. That would mark a historic shift in credit markets, driven in large part by the need to fund AI infrastructure.
Still, investors are beginning to ask how much more they can absorb. Some portfolio managers and bankers say appetite remains strong because these are high-quality borrowers with liquid bonds. But the concern is not credit quality so much as volume. If the same companies keep coming back repeatedly for larger and larger sums, some investors may begin to worry about concentration, future financing needs and whether debt levels will outgrow cash generation. Recent stock-sale announcements suggest equity needs may be rising too, reinforcing the idea that AI’s capital demands are still accelerating.
The AI debt story is a new phase of the boom: the spending race is no longer just pushing up valuations and capital expenditures, it is transforming global fixed-income markets. Banks are expanding into new currencies and inventing new deal structures because the financing needs are so large. For now, investors are still buying. But if AI borrowing keeps climbing at this speed, the next question will be not whether the market wants the debt, but how much more it can realistically take.
