NEW YORK, Nov 21. A wave of aggressive borrowing by America’s largest technology companies is raising concerns on Wall Street. Investors worry that the rapid growth in public debt associated with artificial intelligence infrastructure could stretch the U.S. corporate bond market and eventually hurt the appeal of Big Tech stocks.
These concerns arise even though most hyperscalers, which are the large cloud and AI platform operators, still have relatively low leverage. However, the sudden increase in bond issuance to fund data centers and AI hardware has led to questions about the long-term viability of AI spending and whether the markets can absorb this unprecedented influx of corporate debt.
Big Tech’s Funding Playbook Is Changing
In a shift from the cash-rich strategy that traditionally defined Silicon Valley, tech giants are now turning to public debt markets to fuel the AI competition. Since September, four of the five major hyperscalers—Alphabet, Meta, Oracle, and Amazon—have issued nearly $90 billion in new bonds, according to calculations based on publicly available data.
Alphabet raised about $25 billion, Meta raised $30 billion, Oracle added $18 billion, and Amazon recently priced $15 billion. Notably, Microsoft is the only other hyperscaler that has not joined this latest debt wave, although it remains one of the wealthiest companies in cash.
The sharp increase in borrowing reflects the high cost of building and maintaining AI-ready data centers, which require power-hungry GPUs, customized networking infrastructure, and effective cooling systems. The expenses for these facilities have surged as global demand for AI computing rapidly rises.
Investor Anxiety Builds Despite Strong Balance Sheets
For now, investors claim they are not worried about the immediate effects of these fundraising activities on stock values. The hyperscalers are lightly leveraged compared to their huge revenue bases, and their core businesses continue to generate strong cash flow.
However, the speed and scale of borrowing, rather than the actual debt levels, are raising concerns.
“There’s a lot of hyperscaler issuance coming out, and I think the market has realized that private credit markets won’t fund AI. It’s not going to be free cash flow,” said Brij Khurana, a portfolio manager at Wellington Management Company. “The capital has to come from somewhere, and it will need to come from public bond markets.”
Khurana noted that this shift in financing could also affect stock flows. “What’s happening is a recognition that you need money shifting from stocks into bonds,” he explained, pointing out the developing tension between equity valuations and bond-market dynamics.
Analysts at BofA Securities reported a remarkable jump to over $120 billion in hyperscaler debt issuance this year—up from an average of just $28 billion over the last five years. This includes Meta’s $27 billion private financing deal with Blue Owl Capital in October to support its largest data center project to date.
AI Spending Boom Meets Market Realities
This borrowing surge occurs as U.S. equity markets adjust after six months of steady gains, partly driven by excitement around AI. A pullback in November has highlighted concerns that AI-related capital expenditures might be outpacing actual returns.
The S&P 500 is up more than 11% for the year, but rising doubts about whether AI investments will yield short-term profits have dampened investor enthusiasm.
“There are new doubts emerging about the AI spending narrative,” said Larry Hatheway, global investment strategist for Franklin Templeton Institute. “These concerns involve the need for companies to finance their AI goals, which increasingly includes debt financing.”
Research from Sage Advisory indicates that AI capital expenditures are set to rise to $600 billion by 2027, up from just over $200 billion in 2024 and less than $400 billion in 2025. Net corporate debt issuance is expected to hit $100 billion in 2026, underlining the intensity of the AI competition.
Not All Tech Firms Are Adding Debt – Some Are Cutting
While hyperscalers ramp up borrowing, other key players in the AI ecosystem are taking a different approach.
Nvidia, the leading supplier of AI chips, has reduced its long-term debt from $8.5 billion in January to $7.5 billion at the end of the third quarter. S&P Global Ratings recently improved Nvidia’s outlook to “positive,” citing strong revenue growth and exceptional cash flow.
This divergence shows how differently companies are positioned in the AI value chain. Hyperscalers are investing heavily in AI infrastructure, while suppliers like Nvidia benefit from soaring demand for their hardware.
Regarding recent bond sales, Amazon stated that proceeds would be allocated to business investments, capital expenditures—including AI—and repayment of maturing debt. Microsoft and Oracle did not comment, and Alphabet and Meta did not respond immediately.
Bond Market Feels the Strain as Supply Floods In
Demand for Big Tech’s latest bond offerings has been steady. However, the sudden increase in supply has compelled issuers to offer better terms to attract investors.
Both Alphabet and Meta had to provide 10 to 15 basis points more than their existing debt during their recent offerings, according to a note from Janus Henderson. This premium indicates that investors are becoming more cautious as supply increases, even though credit risk remains low.
Historically, U.S. investment-grade credit spreads have stayed tight due to resilient corporate balance sheets and strong investor demand. But lately, spreads have widened slightly, reflecting the challenges of absorbing such large amounts of new debt issuance in a short time.
“For much of the year, credit spreads have been tightening,” Janus Henderson noted. “But the recent surge in supply—especially from the tech sector—may have changed the landscape.”
Can the Debt Market Sustain AI’s Growth?
Despite the worries, analysts maintain that cash flow remains the foundation of hyperscaler spending, with debt acting mainly as a secondary financing option.
A recent UBS analysis estimated that 80 to 90% of hyperscaler capital expenditure continues to come from operating cash flows rather than borrowing. Even with this year’s increase in debt, these companies’ leverage remains historically low.
Goldman Sachs analysts highlighted in a report that major tech firms still have significant financial flexibility. Excluding Oracle, hyperscalers could collectively take on up to $700 billion in additional debt and still comfortably fit within the leverage profile of an A+ rated company.
“Supply bottlenecks or investor appetite are more likely to act as limits on near-term capital expenditures than cash flows or balance sheet capacity,” Goldman’s analysts wrote.
Garrett Melson, a portfolio strategist at Natixis Investment Managers Solutions, echoed this sentiment: “These companies have strong business lines generating plenty of cash.”
The Bigger Picture: AI at an Inflection Point
The current tensions in the bond and equity markets reflect a broader, fundamental question: Is the expected economic payoff from AI close enough to justify the high capital costs of today?
The speed of spending—driven by competition among tech giants to secure GPU supply, build data centers, and expand cloud infrastructure—may outpace the speed at which AI products produce significant revenue. Investors are starting to examine the timeline for monetization more closely, especially as companies like Google and Meta continue investing billions in unproven AI consumer services.
If AI returns materialize slower than anticipated, high capital costs could eventually pressure corporate earnings. Conversely, if returns come more quickly, today’s rush to incur debt could lay the groundwork for a period of significant profitability.
For now, markets are in a delicate balancing act: enthusiastic about AI’s potential but cautious about the costs of reaching that potential.
Conclusion: A Market Bracing for What Comes Next
The surge in AI-related borrowing represents one of the largest and fastest shifts in tech financing in recent years. While hyperscalers maintain strong financial fundamentals, the unprecedented scale of bond issuance has created new pressures in the market, raising questions about sustainability, investor interest, and the true economic value of AI.
As AI spending accelerates toward an estimated $600 billion annually within three years, the interaction between debt markets, equity valuations, and corporate balance sheets will become more critical to the future of Big Tech.
For investors, the message is clear: the AI boom is no longer just a narrative about innovation and technology change—it’s now a story about financing, debt, and the ability of global markets to handle the costs of building the next generation of digital infrastructure.
