Big Tech’s $400 bn AI debt binge adds pressure on borrowing costs

Reports coming in for today mention that Big US technology firms, especially those investing heavily in AI infrastructure- Amazon, Microsoft, Alphabet, Meta and Oracle- are borrowing on a huge scale to fund their AI build-out.

The five major hyperscalers are anticipated to offering around $250 billion of bonds in 2026 and another $400 billion in 2027, according to Goldman Sachs. The numbers highlight how quickly debt has become an important source of funding for the AI investment boom.

Looking a bit further out, Bank of America market watchers had earlier projected that the ‘Big Five’ hyperscalers might borrow roughly $140 billion per year over the next three years, with some scenarios taking annual issuance above $300 billion as AI capital expenditure accelerates.

So, the near-term picture is clear: hundreds of billions of dollars of corporate borrowing a year, with 2026 already at record marks and 2027 potentially even bigger if AI spending plans hold.

“This level of borrowing is large enough to create another significant source of high-quality bond supply competing for institutional set-income capital. The competitive pressure becomes particularly important at the longer end of the market, and we have already noted borrowing costs climb somewhat,” stated Madhupam Krishna, a SEBI-registered investment adviser and founder of WealthWisher Financial Planners and Advisors.

The US government is issuing a giant stack of bonds to fund itself, while a handful of highly rated technology firms are bringing unusually large volumes of corporate debt to market. Both are competing for institutional set-income capital, although corporate bonds carry additional credit risk and are as a result not perfect substitutes for Treasuries.

US Treasuries and high-quality tech corporate bonds are both bought by similar institutional market participants: pension funds, insurers, mutual funds, asset managers and foreign market participants, among others. That means the sharp gain in the supply of bonds perceived as relatively safe and liquid could put some pressure on the broader set-income market, particularly at the long end- 10-year, 20-year and 30-year maturities.

Krishna stated, “These firms used to fund most investments from their own (internal) cash flow. Now their AI data-centre build-out is so large that capital expenditure is putting greater pressure on internal cash generation, so they’re tapping debt markets.”

Evidence already reveals market participants are demanding a elevated premium to absorb the additional supply. Median spreads on two- to four-year bonds issued by Amazon, Alphabet, Meta and Oracle rose to around 40 basis points from 30 basis points in 2025, according to Reuters.

Demand for hyperscaler bonds has additionally softened. Reuters noted that cover ratios for hyperscaler bond sales declined from nearly five times in February to below two times in July, suggesting market participants are becoming less willing to absorb the rapidly expanding supply without demanding better pricing.

“Median spreads on 2-4 year bonds for Amazon, Alphabet, Meta and Oracle rose to 40 basis points from 30 basis points in 2025 as supply surged. The scale of issuance is beginning to change how market participants look at these firms, with some of their debt increasingly being viewed as among the highest-quality corporate alternatives to government bonds. That’s a meaningful shift,” stated Krishna.

Despite the scale of the borrowing, most market strategists do not see hyperscaler debt issuance alone as a major driver of Treasury yields. The direct effect is likely to be modest, with the The US central bank, the US fiscal deficit and Treasury supply still the main drivers of government bond yields.

Krishna estimates that the additional corporate supply could add roughly 5 basis points to broader borrowing costs, but sees the direct impact on US Treasury yields themselves as marginal.

“The hope lies in the possibility that the duration impact of this corporate borrowing could resemble, to some extent, the effect of quantitative tightening by the Fed. This suggests that the wave of corporate borrowing could raise broader corporate borrowing costs, although the impact on US Treasury yields would likely be much smaller,” further noted Krishna.

The distinction is important. When firms offering large amounts of long-dated bonds, market participants must absorb that additional duration. If demand does not keep pace with supply, corporate yields and spreads can climb. But that does not automatically translate into a similar gain in Treasury yields.

The US Treasury market is additionally vastly larger than the hyperscaler bond market. The Treasury market has more than $30 trillion of outstanding debt, meaning even several hundred billion dollars of additional corporate issuance is relatively small compared with the government’s overall borrowing needs.

The bigger drivers of Treasury yields as a result stay The US central bank policy, including the interest-rate path and balance-sheet runoff; US fiscal deficits and Treasury issuance; inflation expectations; and global demand for US safe-haven assets.

But the hyperscaler borrowing boom is still worth watching.

If Goldman Sachs' projection of $400 billion of hyperscaler bond issuance in 2027 materialises, it would mark a dramatic change from the industry's historical reliance on internal cash flows. And if AI infrastructure spending keeps expand, the borrowing could spread beyond the five hyperscalers to data-centre operators, utilities, chipmakers and other firms building the infrastructure required for the AI economy.

That could create a much broader wave of long-duration corporate debt supply at a time when the US government itself is selling enormous quantities of long-term Treasuries.

"For now, Big Tech’s AI borrowing boom is unlikely to be the main reason Treasury yields climb. But it is becoming an increasingly important marginal factor, one that could make it more expensive for both firms and the US government to mobilize long-term money if the supply of debt keeps surge," stated Krishna.

“For market participants, that means watching not just Fed policy and fiscal deficits, but additionally the pace of AI‑related corporate debt issuance when assessing the outlook for long‑term bond yields and duration risk,” further noted Krishna.