Governments have long had the bond market's biggest borrowing appetite more or less to themselves. That era is fading: the world's largest technology companies are now competing with sovereign issuers—above all the US government—for the same pool of investor capital.

Amazon, Alphabet, Meta, Microsoft and Oracle are borrowing heavily to fund artificial intelligence infrastructure, placing them in direct competition with sovereign borrowers for investor cash.

The Numbers Behind the Borrowing Spree

Four of the largest US technology companies plan to spend roughly $650 billion on AI infrastructure in 2026. Broadening the view to all hyperscalers—the companies operating the largest cloud and data-center platforms—capital expenditure estimates for the year exceed $800 billion and reach as high as $1.1 trillion. The outlays reflect the physical requirements of AI data centers: specialized chips, large construction programs and substantial power capacity.

AI-linked corporate debt issuance is reported to have reached approximately $450–500 billion in the first nine months of 2026, more than double the pace of previous years.

Analysts at Goldman Sachs and Morgan Stanley expect the trend to escalate, with Goldman Sachs projecting that hyperscaler AI debt issuance could push toward or above $1 trillion in 2027.

Much of this spending is also being kept off balance sheets. Tech firms have moved more than $120 billion of AI data center spending out of their accounts through special purpose vehicles, or SPVs, and leasing arrangements. An SPV functions as a separate company created to own the asset and carry the debt: the tech giant uses the data center and pays for it over time, while the borrowing sits elsewhere. In aggregate, undisclosed lease and purchase commitments for major hyperscalers exceed $1.5 trillion.

From Cash-Funded Growth to Leveraged Bets

The turn to bond markets marks a break with recent practice: the largest technology companies have historically financed capital expenditure primarily from operating cash flow rather than large-scale debt issuance. Bond buyers have taken notice, and even investment-grade names, a category denoting lower perceived credit risk, are paying up. Investors are demanding yields above 7% from Meta, a company that is not exactly short on revenue.

Oracle offers a sharper warning sign. Based on recent credit default swap spreads, the company's implied five-year default risk has moved above 20%. CDS contracts work like insurance against a borrower failing to pay; when that insurance becomes more expensive, the market is signaling greater worry.

All of this is unfolding against a heavy macroeconomic backdrop. Global debt hit a record $365.5 trillion in the first half of 2026, and the United States continues to run high fiscal deficits, meaning the US Treasury needs a steady stream of buyers for new government debt. Treasury yields also serve as a reference point for pricing corporate debt, so the buyer base for government bonds matters well beyond the Treasury market itself.

What This Means for Borrowers, Investors and the US Treasury

Capital is finite, even in a market as deep as US fixed income. When hyperscalers issue hundreds of billions of dollars in new bonds, they are courting many of the same pension funds, insurers and asset managers that buy Treasurys and other sovereign debt.

The off-balance-sheet structures add a transparency problem. Investors pricing a hyperscaler's bonds may not see the full scope of its commitments, and the more than $1.5 trillion in undisclosed lease and purchase obligations is precisely the kind of figure that tends to matter most when sentiment turns.

For investors, a few signals are worth watching. Credit rating actions on the major hyperscalers are one, since downgrades could move both bond prices and stock prices. CDS spreads, particularly for Oracle, offer a real-time read on how nervous lenders are becoming. Treasury auction demand is another: if government debt sales start drawing weaker interest while tech issuance stays strong, the competition for capital will move from theory to measurable fact.