The revolution of the so-called hyperscalers is reaching increasingly colossal proportions. Technology companies’ bet on artificial intelligence is measured in hundreds of billions of dollars – investments that until recently came exclusively from astronomical, but limited, profits. The sector still needs more data centers and has started turning to debt markets to finance them, raising investor concerns and chilling the market’s previously warm embrace of the technology.
Oracle, the most indebted of the big players and which has tied its future to contracts with OpenAI, is at the center of these doubts: its shares have fallen by 33% compared to their September peak. Its debt is also taking a hit, trading below par, while credit default swaps on its bonds – a measure of financial risk – have risen to levels not seen in three years, dragging with them those of other companies with high AI exposure and weaker credit history.
The market expects an excess of debt and has gone on alert; Financing investments with borrowed money is very different from financing them with multimillion-dollar profits. According to JP Morgan estimates, building the global data center and AI infrastructure, along with the necessary energy supplies, will cost more than $5 trillion by 2030. Of this total, only $1.5 trillion will come from companies’ organic cash flow; the rest will require major tech companies to turn to the capital markets. “It will be an extraordinary and long-lasting event in the capital markets,” concludes the bank.
The bank estimates that over the next five years the major technology companies exposed to artificial intelligence – Alphabet, Amazon, Microsoft, Meta and Oracle – will have to issue $1.5 trillion in bonds, with $300 billion expected in 2026 alone, more than half of what the US Treasury issues. “If anything like our predictions come true, AI and data center-related industries could account for more than 20% of the market by 2030,” the report notes.
For now, in September and October alone, the tech giants raised $75 billion in investment-grade bonds, and are expected to end the year issuing more than $200 billion in debt, both through private placements (to venture capital funds with less transparency) and through public markets. All this is aimed at financing 380 billion dollars in investments to build infrastructure related to artificial intelligence.
So far, Oracle and Meta have shown the greatest ability to fund their AI strategies, followed by Alphabet (despite Google’s parent company holding $100 billion in cash). Alphabet kicked off in May with an $11 billion issuance, followed in September by Oracle with a $15 billion issuance on record demand. In October, Meta raised $30 billion in bonds and another $27 billion through private market deals to finance a data center in Louisiana, US. This was done via a special purpose vehicle (SPV), allowing a company to finance a specific project without the debt appearing on its balance sheet.
This emergency has prompted UBS to express “concentration risk concerns,” as the problems are concentrated in a handful of companies: Meta, Oracle, Alphabet, Broadcom and Dell. Spreads on some of these bonds are already widening. In response, banks are deploying a variety of exotic financial instruments, including data center-backed mortgage bonds and ABS (asset-backed securities). Bank of America estimates that the data center securitization market could reach $110 billion next year.
Increasing investments and doubts about profitability
Meta founder Mark Zuckerberg revealed that the company will invest approximately $600 billion in AI-related infrastructure in the United States alone; in 2025 alone, it plans to spend $71 billion, a figure it expects to nearly double by 2027. For now, it has some leeway: It plans to increase its debt fourteen-fold over this period (from $4 billion to $59 billion). However, this will come at the expense of its share buyback programs – which will fall from $35 billion to $5 billion – and reduce free cash flow by more than half.
Oracle’s AI bet, driven by its deal with OpenAI, has made it, in just a few quarters, the most indebted investment-grade technology company and the only one with negative cash flow. While stressing that its debt maturities are manageable, JP Morgan warns of rising interest rates and large investment commitments ahead.
Revenue pressure increases risk: By 2028, a third of its revenue will come from a single customer, OpenAI. This scenario has led Barclays to predict that ratings agencies may downgrade Oracle to BBB– (S&P and Moody’s have already put it on a negative outlook), just above junk status, and that the company may have to turn to private debt markets, which are less transparent and more expensive. The British bank even recommends buying credit default swaps (CDS) on Oracle, a signal that has already pushed its CDS higher. Bondholders have seen losses of up to 7% in just over six weeks.
This instability is also affecting other tech companies exposed to AI but with weaker credit histories, though not major hyperscalers, which remain largely isolated. Coreweave, which is backed by Nvidia and holds significant contracts with Meta, has seen its shares plunge 30% in a week, while five-year CDS on its bonds have risen 13% in the same period.
JP Morgan also questions whether these massive investments will generate real profitability. According to the report, achieving a 10% return on all required investments over the next five years would require major tech companies to generate $650 billion in annual revenue forever. “A huge amount,” the report notes, equivalent to $180 per month for each Netflix subscriber or $34.72 for each current iPhone owner. “Even if everything works out, there will be (he continues) spectacular winners, and probably some equally spectacular losers,” he adds.
Adding to concerns about profitability is the potential systemic impact of artificial intelligence on the market. The Bank of England recently noted that while the sector’s systemic impact has so far been limited – concentrated mainly in stock market gains – the high financing needs of these companies could influence both the debt market and commodity markets, particularly copper, which is heavily consumed in data centers and artificial intelligence infrastructure.
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