AI Debt Risks Mount: Why Borrowing by Meta, Alphabet, Microsoft and Oracle Worries Investors

TradingKey - The artificial intelligence race is gradually evolving from a contest of technology and capital expenditures into a competition of financing capabilities. As data center scale continues to expand, Meta (META), Microsoft (MSFT), Oracle (ORCL), and Alphabet (GOOGL) have begun entering the bond market more frequently to raise funds for servers, AI chips, power facilities, and high-speed networks.

In the past, large tech companies primarily relied on operating cash flow to support expansion. Today, quarterly capital expenditures at some companies are approaching or even exceeding operating cash flow. Relying solely on internal funds could not only deplete cash reserves, but also squeeze room for share buybacks, mergers and acquisitions, and other strategic investments. By issuing long-term bonds, tech giants can spread buildout costs into the future and lock in urgently needed computing power and energy resources ahead of time.

The issue is that as more companies borrow at the same time, bond investors will demand higher returns. Once financing costs continue to rise, pressure could transmit from credit markets to corporate profits, free cash flow, and even tech stock valuations.

Why Tech Giants Rely on Debt to Build AI?

Data centers are an infrastructure business that requires massive upfront capital expenditure and entails long payback cycles. Land, power access, building construction, cooling equipment, servers, and AI chips all require capital outlays before a project generates revenue, and it often takes months or even years from breaking ground to achieving stable cash flow.

Although major cloud computing companies possess strong balance sheets, their capital expenditures are approaching operating cash flows. Goldman Sachs estimates that by 2026, roughly one-third of hyperscalers' capex will be funded through debt, and this proportion could rise to 35% in 2027. As capital investments converge with internal cash-generation capacity, issuing bonds has become a critical choice for maintaining construction momentum and preserving cash reserves.

From a corporate perspective, taking on debt does not necessarily signal a deteriorating financial position. For tech giants with high credit ratings, the bond market provides large-scale, long-term capital, helping them spread out capex pressure and avoid depleting substantial cash reserves at once. As long as future revenue from cloud computing, advertising, and AI services can gradually cover investment costs, debt financing can remain a standard capital allocation tool.

However, the problem is that the scale of AI infrastructure investment has far surpassed previous expansion cycles in the tech industry. Goldman Sachs projects that debt supply from hyperscalers will reach $296 billion in 2026 and is expected to further increase to $440 billion in 2027. In other words, the bond market must continuously absorb a substantial volume of new debt issued by the tech sector.

Will AI Debt Become a New Risk for the Bond Market?

The bond market first faces price pressure from increased supply.

When companies such as Meta, Microsoft, Alphabet, Oracle, and Amazon issue bonds in heavy concentration, investors must allocate funds across more new issues. To attract buyers, issuers may have to offer higher yields. Rising yields on new debt also make previously issued comparable bonds relatively less attractive, putting pressure on secondary market prices.

This change is already reflected in credit spreads. According to Bank of America data, as of the end of October 2026, AI-related bonds accounted for 5.14% of the investment-grade corporate bond index, up from 2.73% at the beginning of 2025. This shows that AI financing has gradually evolved from a relatively concentrated industry theme into an important factor influencing the broader corporate bond market.

In terms of yields, the spread of AI-related investment-grade corporate bonds over US Treasuries has recently been around 148 basis points, compared with about 77 basis points for other investment-grade corporate bonds. The 71-basis-point difference indicates that investors demand higher risk compensation when holding AI-related bonds.

Widening credit spreads do not mean issuing companies are about to default. For cash-rich giants like Microsoft and Alphabet, the market demand for higher yields is likely mainly related to concentrated new bond supply, changes in investor positioning, and concerns over the return-on-capital cycle of AI. However, for emerging computing-power companies that need continuous financing to build data centers, rising borrowing costs could directly impact project economics.

Another notable change is that AI financing is expanding from traditional investment-grade corporate bonds to high-yield bonds, leveraged loans, and private credit. Bank of America estimates that AI-related funding raised through credit markets could reach $685 billion in 2027, up about 31% from 2026, with the incremental growth primarily coming from private credit.

Which AI Stocks Face Greater Financial Risks?

Note: Financial reporting periods vary across companies; debt and cash figures are based on their respective most recently disclosed balance sheets, while capital expenditures and free cash flow correspond to their most recent reported quarters or annual guidance.

Microsoft currently possesses the most ample financial cushion. In its most recent quarter, operating cash flow stood at approximately $58.0 billion, leaving nearly $18.6 billion in cash headroom after deducting capital expenditures. By the end of the quarter, the company also held approximately $64.5 billion in cash and short-term investments. Therefore, Microsoft's bond issuance is closer to a proactive optimization of its financing structure rather than filling an imminent funding gap.

Alphabet's risk profile remains moderate. The company benefits from massive cash flow generated by its search advertising and cloud computing businesses, yet its capital expenditure growth has outpaced current operating cash flow. As of the end of September, the book value of Alphabet's long-term debt stood at approximately $125.1 billion. In the first nine months of 2026, it issued a cumulative total of approximately $80.8 billion in U.S. dollar and foreign currency bonds, followed by another €6 billion bond issuance in November.

However, compared with less profitable data center operators, its advertising and cloud businesses still provide strong debt service coverage. Its short-term risks stem primarily from declining returns on capital expenditures rather than a liquidity shortfall.

Meta likewise possesses strong cash-generation capabilities, but its long-term contractual obligations warrant closer attention. As of the end of the third quarter, the company's long-term notes balance stood at approximately $84.0 billion, while unfulfilled non-cancelable contractual commitments reached approximately $454.5 billion, a substantial portion of which is tied to data centers, cloud services, and infrastructure leases.

These commitments will not all translate into debt immediately, yet they will constrain Meta's flexibility to cut spending in the future. Even if AI revenue growth falls short of expectations, the company may still need to continue fulfilling certain lease and purchase contracts. Therefore, Meta's core risk lies not in its current debt service capacity, but in whether its locked-in long-term spending can generate sufficient returns.

Among the four companies, Oracle faces the greatest funding pressure. Its latest quarterly capital expenditures reached approximately $28.5 billion, surpassing its operating cash flow of $23.1 billion and driving free cash flow down to around -$5.4 billion. In addition to recently issuing $10 billion in bonds, the company plans to raise a similar amount through equity financing, indicating that a single financing channel is no longer sufficient to fully cover its expansion needs.

If its AI cloud business grows smoothly, these investments could bolster Oracle's competitiveness in the data center market; however, if projects are delayed, customer demand weakens, or financing costs continue to rise, the pressure on Oracle's profits and earnings per share could be significantly higher than that on Microsoft, Alphabet, and Meta.