America's largest technology companies are increasingly relying on debt to finance the massive infrastructure required for the artificial intelligence boom. With nearly $500 billion in AI-related debt issued in 2026 alone, credit markets are beginning to signal caution regarding the financial commitments of these tech giants.
Rising Debt and Investor Concern
The AI race, demanding extensive data centers, advanced chips, and computing power, is no longer solely funded by soaring stock valuations or corporate cash reserves. Estimates suggest the 'Magnificent Seven' tech firms have collectively accumulated over $600 billion in debt. In 2026, Big Tech companies issued approximately $200 billion in corporate bonds, nearly doubling the amount raised in all of 2025.
This escalating debt has led to a sharp increase in the cost of insuring against a potential default, as indicated by five-year credit default swap (CDS) spreads. These spreads, which reflect investor concern over credit risk, have risen broadly for major AI-linked technology companies, including Oracle, Broadcom, Meta, and Nvidia.
Oracle Leads CDS Spread Increases
- Oracle: Its five-year CDS jumped 70 basis points in 2026, reaching around 215 basis points, the largest increase among tracked major tech firms.
- Broadcom: Saw a 48-basis-point increase.
- Meta: Its CDS climbed 39 basis points to approximately 95 basis points, its highest since trading began in October 2025.
- Nvidia: Experienced a rise of about 32 basis points to roughly 82 basis points, also a record high since November 2025.
- Amazon and Alphabet: Their CDS spreads rose by around 30 and 29 basis points, respectively.
While rising CDS spreads don't imply imminent default, they signal that investors are demanding a higher premium to protect against potential deterioration in creditworthiness.
The Enormous AI Infrastructure Bill
At the core of these concerns is the sheer scale of investment needed for AI infrastructure. Hyperscalers are in a fierce competition to build new data centers, acquire cutting-edge computing equipment, and secure vast amounts of energy to power increasingly sophisticated AI models.
Goldman Sachs Research estimates that nearly $500 billion of AI-related debt has been issued so far in 2026, underscoring the deep integration of credit markets into the technology investment cycle.
For years, major tech companies were known for their robust cash reserves. However, the economics of the AI race are pushing them towards a different funding model, increasingly relying on corporate bonds and other forms of borrowing for long-term projects rather than just cash flow or equity issuance.
Uncertain Returns and Hidden Liabilities
The risk extends beyond just the debt amount. It encompasses the combination of rising leverage, massive capital expenditure, and the inherent uncertainty surrounding the eventual returns from AI infrastructure investments. Data centers require billions upfront and can take years to generate sufficient returns, while rapidly evolving technology risks making current infrastructure less economically viable before costs are recovered.
Further compounding concerns, a Nikkei Asia investigation reported that Alphabet, Microsoft, Amazon, Meta, and Oracle combined could have approximately $1.65 trillion in liabilities outside their public balance sheets, compared to roughly $1.35 trillion officially disclosed in the previous quarter. Meta alone reportedly accounts for about $420 billion of these estimated off-balance-sheet liabilities. While these figures include various contractual commitments and not just conventional debt, they highlight the immense financial obligations supporting the AI buildout.
A New Test for the AI Boom
Issuing new shares is another funding option, but it comes at the cost of diluting existing shareholders. If investors begin to question the returns from AI spending, this dilution could further pressure valuations.
The ultimate question for the AI boom is not whether companies like Nvidia, Microsoft, Amazon, or Alphabet can service their debts today—their scale and cash generation remain substantial. Instead, it's whether the returns generated by the AI infrastructure will ultimately justify the extraordinary capital commitments being made.