A wave of borrowing has swept through the technology sector, with U.S. companies issuing more than $200 billion in bonds this year to finance a massive build-out of artificial intelligence infrastructure. This surge in debt is reshaping corporate credit markets as tech giants shift from using their own cash to tapping investors to fund long-term AI projects.
Major players like Meta and Oracle are leading the charge, raising tens of billions of dollars to construct the data centers and acquire the computing power necessary for the next generation of AI. The scale of this borrowing now accounts for a significant portion of the entire U.S. corporate debt market, prompting analysts to examine the potential long-term risks.
Key Takeaways
- U.S. companies have issued over $200 billion in bonds specifically for AI-related projects this year.
- Meta's recent $30 billion bond sale attracted a record-breaking $125 billion in orders from investors.
- AI-related bond sales now represent more than a quarter of all net U.S. corporate debt supply in 2024.
- Analysts are raising concerns about market concentration, debt sustainability, and the risks of funding rapidly depreciating assets.
The AI Arms Race Hits the Bond Market
Historically, Big Tech companies have relied on their substantial earnings and large cash reserves to fund major investments. However, the enormous upfront costs associated with developing large-scale AI capabilities have prompted a strategic shift towards debt financing. Since the financial returns on these AI investments may not materialize for several years, companies are turning to capital markets to manage the expense.
This trend was highlighted by Meta's recent bond sale, which raised $30 billion to support its AI initiatives. The offering was met with unprecedented investor appetite, drawing approximately $125 billion in orders. According to sources close to the deal, this represents the largest demand ever recorded for a U.S. investment-grade corporate bond.
By The Numbers
Goldman Sachs estimates that large bond sales by companies including Meta, Alphabet, and Oracle have contributed to AI-related issuance making up more than 25% of the net supply of U.S. corporate debt this year.
Oracle also tapped the market in September, selling $18 billion in bonds. The proceeds are intended to help finance the development of data centers leased to provide computing power for AI leader OpenAI. This move underscores a growing trend of infrastructure development being funded by debt to serve a concentrated, high-demand client base.
A Market Hungry for Tech Debt
The massive bond sales are occurring at a time of high demand for corporate credit. Earlier this year, U.S. credit spreads—the difference in yield between corporate bonds and government securities—reached their lowest levels in two decades, making it an attractive time for companies to borrow.
"This pick-up in issuance is occurring at a time when inflows into the asset class remain firm, helping to absorb new paper," said Jason Borbora-Sheen, a portfolio manager at asset manager Ninety One.
This strong investor demand helps companies secure the vast sums needed for their AI ambitions. However, some market observers believe this influx of tech debt could have wider implications. Gordon Shannon, a fund manager at TwentyFour Asset Management, noted the potential for this trend to divert capital from other sectors.
"The highly rated tech issuers’ huge appetite for debt to fund AI investment will divert demand from other areas of the corporate credit markets," Shannon explained.
Analysts Warn of Emerging Risks
While the market is currently absorbing the new debt, senior fund managers and analysts are beginning to question the long-term sustainability of this spending boom. The central concern revolves around whether the eventual returns from AI will justify the hundreds of billions of dollars in debt being accumulated.
A Systemic Concern?
The core issue is whether companies are taking on massive debt to build infrastructure tied to a single, unproven technological wave. If the AI boom turns into a bubble, the debt could remain long after the assets it funded have lost their value.
Gil Luria, head of technology research at DA Davidson, pointed to the potential for systemic risk. He warned that companies are committing to enormous projects for a very limited customer base and will need to raise hundreds of billions more in the future.
"If the markets end up investing hundreds of billions of debt in rapidly depreciating assets that may not have sufficient returns, the risk could become systemic," Luria stated.
Other experts are raising similar flags. Fraser Lundie, global head of fixed income at Aviva Investors, said the surge in issuance brings up "important questions about concentration risk [and] capex sustainability." He also suggested that the long-term nature of these bonds could make the broader credit market more sensitive to changes in interest rates.
Kevin Thozet, a member of the investment committee at Carmignac, warned of the consequences if the AI boom leads to widespread defaults. "If this leaves much more bad debt in the system, it could have more negative consequences," he said, adding that the use of private debt for some financing makes the situation "quite opaque."
The Floodgates May Just Be Opening
The current wave of AI-related debt may only be the beginning. In a recent note, analysts at Barclays described the potential for future issuance as the "largest elephant in the room" for investors.
"Surging capex volumes could finally break the dam and lead to a flood of issuance that we have not previously forecast," the Barclays note read. The sentiment is shared by Goldman Sachs, whose analysts have predicted that 2025 will be "a banner year for AI-linked net issuance," with the trend continuing into 2026.
As tech companies continue to pour capital into the AI race, the corporate bond market has become a critical battleground. For now, investors are eagerly financing the future of technology, but the long-term consequences of this multi-billion-dollar gamble remain to be seen.