Nearly $500 billion in debt issued in 2026: Is big tech borrowing too much for AI boom?

The AI boom is no longer being financed only by soaring stock valuations and massive corporate cash piles. Increasingly, America’s biggest technology companies are turning to debt to fund the data centres, chips and computing infrastructure needed to keep pace in the artificial intelligence race — and credit markets are beginning to take notice.

The Magnificent Seven have accumulated more than $600 billion in debt, according to estimates cited in the material, while Big Tech companies have issued around $200 billion in corporate bonds so far in 2026, nearly twice the amount raised during the whole of 2025.

Now, the cost of insuring that debt against a potential default is climbing sharply.

The chart, based on S&P Global Market Intelligence/LSEG data as of July 28, shows a broad rise in five-year credit default swap (CDS) spreads for major AI-linked technology companies. The increase has been particularly pronounced for Oracle, Broadcom, Meta and Nvidia.

Oracle leads the surge 

Oracle has emerged as the biggest flashpoint. According to The Kobeissi Letter, Oracle’s five-year CDS has jumped 70 basis points in 2026, reaching around 215 basis points — the largest increase among the major technology companies tracked.

Broadcom follows with a 48-basis-point increase, while Meta’s CDS has climbed 39 basis points to around 95 basis points, its highest level since trading began in October 2025.

Nvidia’s five-year CDS has risen about 32 basis points this year to roughly 82 basis points, also its highest level since trading began in November 2025.

Amazon and Alphabet have seen their CDS spreads rise by approximately 30 and 29 basis points, respectively.

A CDS is essentially a financial contract that provides protection against a borrower defaulting on its debt. When investors demand a higher premium for that protection, it can signal growing concern about the borrower’s credit risk.

That does not mean these companies are expected to default. Rather, the widening spreads suggest investors are assigning a higher cost to protecting themselves against potential deterioration in creditworthiness.

The AI infrastructure bill is getting bigger 

At the centre of the concern is the sheer scale of spending required to build the infrastructure underpinning the AI boom. Hyperscalers are racing to construct data centres, acquire advanced computing equipment and secure the enormous amounts of power required to run increasingly sophisticated AI models.

Goldman Sachs Research estimates that nearly $500 billion of AI-related debt has been issued so far in 2026, highlighting how deeply credit markets have become intertwined with the technology investment cycle.

For years, the largest technology companies were viewed as businesses with enormous cash reserves and relatively strong balance sheets. But the economics of the AI race are pushing them toward a different funding model.

Rather than relying entirely on operating cash flow or issuing shares, companies are increasingly using corporate bonds and other forms of borrowing to finance long-term infrastructure projects.

That creates a fundamental question for investors: How quickly will the enormous investments being made today translate into revenues and profits?

Why investors are becoming cautious 

The risk is not simply the amount of debt itself. It is the combination of rising leverage, enormous capital expenditure and uncertainty over the eventual returns from AI infrastructure.

Data centres require billions of dollars upfront and can take years to generate sufficient returns. Meanwhile, the technology itself is evolving rapidly, creating the possibility that infrastructure built today could become less economically attractive before its costs are fully recovered.

An investigation by Nikkei Asia has also raised concerns over liabilities associated with major technology companies that may sit outside conventional balance-sheet measures.

It reported that Alphabet, Microsoft, Amazon, Meta and Oracle together could have around $1.65 trillion in liabilities outside their public balance sheets, compared with roughly $1.35 trillion in liabilities officially disclosed in the previous quarter. Meta was reported to account for about $420 billion of the estimated off-balance-sheet liabilities.

Such figures need to be treated carefully because off-balance-sheet liabilities can include a range of contractual commitments and financing structures and do not necessarily represent conventional debt or an immediate repayment obligation.

Still, they underscore the enormous financial commitments being made to support the AI buildout.

A new test for the AI boom 

Big Tech also has another funding option: issuing new shares. But that comes with its own cost. Additional equity can reduce dependence on borrowing, but issuing large amounts of stock can dilute existing shareholders. If investors begin questioning whether AI spending will generate adequate returns, that dilution could become another source of pressure on valuations.

The bigger concern is therefore not whether companies such as Nvidia, Microsoft, Amazon or Alphabet can pay their debts today. Their scale, cash generation and access to capital remain substantial advantages.

The question is whether the returns from the AI infrastructure boom will ultimately justify the extraordinary amount of capital being committed to it.