Tech companies have borrowed about $500 billion in nine months to finance AI infrastructure, a trend that is contributing to rising U.S. interest rates and worrying investors, with debt forecasts reaching $1.2 trillion by 2027 according to Goldman Sachs.
AI-generated summary
The artificial intelligence sector is experiencing rapid growth in infrastructure investments, requiring significant financing through debt as the cash flow of the tech giants is no longer sufficient.
Artificial intelligence (AI) players have suddenly started borrowing hundreds of billions of dollars, a surge that is contributing to soaring interest rates and investor nervousness. Almost nothing in 2024 and around 500 billion in nine months since January. The technology sector is raising debt with all its might to finance the chips, servers and data centers that form the AI ecosystem.
The immense cash flows generated by tech giants, from Google to Meta, via Amazon and Microsoft, are no longer enough. Goldman Sachs predicts a further increase in speed in 2027, to reach 1,200 billion dollars. “In terms of growth, it’s something we’ve never seen,” assures Chris Della Fave, of the fundraising consulting firm Post Oak, who estimates the share of AI in total private bond issues at 25%, compared to 4% two years ago.
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This year, the ecosystem is expected to have borrowed more than U.S. cable operators to support the entire rise of the internet or railroad companies during the U.S. rail boom, adjusted for inflation. So far, the bond market has digested this flow smoothly, but it has had to pay a price. Even big names like Meta had to offer more than 7% per year, while data center (cloud) specialists went beyond 9%.
“More bonds are being issued. Investors have to absorb more, which means those who borrow have to offer higher returns,” explains Chris Della Fave. And the entire market is concerned, not just the AI builders. “Someone who bought a Treasury bill may decide to buy (debt from) Microsoft,” explains Mark Malek, head of investment at Siebert Financial. “This puts (U.S. government borrowing) rates under pressure.”
This factor is added to the other accelerator of American sovereign rates, namely inflation, fueled by the war against Iran and the high level of energy prices. The rate on 10-year US government bonds, a benchmark on Wall Street, is currently around 5.30%, the highest since 2002.
“Correction risk”
The phenomenon of arbitrage between the two debts, public and private, is reinforced by the fact that until recently speculative funds had accumulated Treasury bills like never before (7% of the total in circulation at the end of 2025). They are likely to reorient their investments more quickly than insurers or pension funds. Even if the war ended and oil prices slowed, Chris Della Fave projects, "I don't think yields would fall dramatically, due to the influence of AI debt."
In addition to the increased cost, some wonder about the risks inherent in AI bonds. A slowdown, even moderate, in the frantic pace of infrastructure development, delays on certain projects or insufficient growth in income could trigger a “massive adjustment” in valuation on the financial markets, of debt but also of stocks, warns Mark Malek. The Bank of England reported, at the end of September, a “risk of a more marked correction” than in July, a month during which the Nasdaq index, with a strong technological composition, dropped almost 7%.
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In this context, the “cloud” specialist Oracle is sometimes considered a leading indicator. Massive debt ($125 billion), cash flow that is crumbling every quarter and a possible schedule slippage on a huge data center project in New Mexico, several lights are red for Larry Ellison's group. “If Oracle has a problem, that they cannot pay” a debt maturity, anticipates Mark Malek, “this could lead to a contagion effect” to the entire AI debt.
AI outlook — possibilities, not facts
AI sector debt to reach $1.2 trillion by 2027, Goldman Sachs predicts
Likely · Within months
Even a moderate slowdown in AI development could trigger a massive valuation adjustment in financial markets
Possible · Within months
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