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Big Tech Borrows $220 Billion for AI as US Treasury Yields Reach 2002 High

Big Tech companies have issued $220 billion in debt for AI infrastructure as U.S. Treasury yields reach their highest level since 2002.
Big Tech companies issue $220 billion in debt to fund AI data centers and models as U.S. Treasury yields reach their highest

Major technology companies have issued about $220 billion in debt this year to finance artificial intelligence infrastructure, including data centers and AI models, as U.S. Treasury yields climb to their highest levels since 2002, according to figures cited by Coin Bureau from Reuters.

Alphabet, Amazon, Meta, Microsoft and Oracle have collectively raised the amount through debt issuance this year, more than doubling last year's total, according to the figures cited in the post. The borrowing comes as the companies commit heavily to the computing infrastructure required to develop and deploy artificial intelligence systems.

Reuters reported that hyperscalers have issued $220 billion in bonds this year, with the surge in corporate borrowing adding to pressure in bond markets already facing higher government borrowing requirements.

AI Investment Adds to Bond Market Supply

The scale of corporate borrowing reflects the substantial financing requirements associated with the expansion of AI infrastructure. Data centers require large amounts of computing equipment, electricity and supporting infrastructure, while AI model development also requires significant investment.

The additional bond issuance comes at a time when government bond yields have risen sharply. Reuters reported on October 1 that the U.S. 10-year Treasury yield reached 5.34%, its highest level since 2002, before retreating to 5.26%. The broader increase in global yields has been linked to inflation concerns, higher energy prices and concerns about government debt levels, alongside growing financing needs for AI infrastructure.

For technology companies, higher yields can increase the cost of issuing new debt. Companies that rely more heavily on borrowing to fund capital expenditure therefore face higher financing costs when bond investors demand greater returns.

Higher Yields Raise Borrowing Costs

The effects of higher Treasury yields extend beyond large technology companies. Treasury rates influence pricing across a wide range of U.S. credit markets, affecting the cost of mortgages, auto loans, student loans and corporate borrowing.

As benchmark government yields rise, lenders and investors can demand higher returns on other forms of debt to compensate for differences in risk. That can translate into higher financing costs for households and businesses, although the effect varies by loan type and individual market conditions.

Reuters reported that elevated bond yields are already increasing borrowing costs for governments, businesses and households. The rise has occurred alongside renewed concerns about inflation and the sustainability of large public and private borrowing programs.

Global Interest Costs Outpace AI Investment

Coin Bureau also cited the Institute of International Finance as saying that major economies now spend more on interest payments than the world invests in AI itself.

The comparison places the scale of global debt-service costs alongside the rapid expansion of AI investment. Reuters separately reported that global government interest payments have topped $3.3 trillion, exceeding spending on defense, AI and clean energy.

The combination of heavy AI-related corporate borrowing and elevated government financing requirements has therefore become part of a broader bond-market debate. For now, U.S. Treasury yields remain at levels not seen since 2002, while technology companies continue financing the expansion of AI infrastructure through large-scale debt issuance.


Writer: Victoria Hale  
Technology & Blockchain Writer

Victoria Hale writes about blockchain technology, digital infrastructure, and the intersection of emerging technologies with finance. Her articles explore how new protocols and systems are shaping the evolving digital economy.

She prioritises clarity and accuracy when explaining technical developments to a general audience.

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