Rising Treasury Yields Drive Up Borrowing Costs
With 10-year U.S. Treasury yields reaching approximately 5.17% in September 2026, the highest level since 2007, companies heavily reliant on debt financing face significantly higher borrowing expenses. This increase represents about a 1 percentage point rise since the start of the year, meaning AI-related companies must offer more lucrative returns to attract investors in debt markets.
JPMorgan Chase projects that AI-linked debt issuance will total $4.1 trillion through 2030, reflecting massive capital needs for data center expansion and AI infrastructure development. As a result, rising yields threaten to elevate costs across the board for firms engaged in this capital-intensive growth.
Debt-Heavy AI and Cloud Companies Feel the Pressure
Debt-dependent companies such as CoreWeave, a neocloud provider that went public last year, have warned of the direct impact rising rates have on their interest expenses. CoreWeave noted in its June 2026 SEC filing that each 100 basis point increase in interest rates could add roughly $30 million to its annual interest costs due to its outstanding floating rate debt.
Meanwhile, Oracle’s stock declined about 7% this week and roughly 30% year-to-date, partly due to concerns over its New Mexico data center project, Project Jupiter. Reports indicated Oracle issued a “force majeure” notice to delay payments if the facility does not come online by 2028, underscoring the strain that higher financing costs and operational delays can impose.
SoftBank’s Costly Junk Bond Sale Highlights Financing Challenges
Japan’s SoftBank, a major financier of AI ventures, recently issued $11.1 billion in junk bonds, with yields reaching 9.75% on the seven-year tranche. This substantial cost of capital underscores the premium investors demand from riskier AI-related debt amid rising interest rates and market uncertainty.
Industry observers note that many AI firms are effectively “price takers” in debt markets, accepting high yields to secure necessary funding. As Mark Malek, CIO at Siebert Financial, observed, these companies must prioritize capital acquisition to remain competitive despite soaring costs, reflecting the aggressive investment environment in AI infrastructure.
Selective Lending Narrows AI Infrastructure Players
Lenders have become increasingly cautious, narrowing their focus to a smaller subset of AI infrastructure firms deemed creditworthy. Riley Thompson, vice president at Mitsubishi HC Capital America, explained that the market’s interest has concentrated on about 20 neocloud companies out of an original roster of 50, reflecting heightened scrutiny even when borrowers offer higher rates.
This selectivity suggests that smaller or less established providers may face difficulties securing financing, potentially consolidating the AI infrastructure landscape around larger or more financially stable players with stronger credit profiles and investment-grade ratings.
Demand for AI Services Remains Robust Despite Challenges
Despite rising debt costs and regulatory challenges, demand for AI services continues to surge. Meta’s Muse personal assistant app, launched in September 2026, achieved over 2.5 million global downloads within two weeks, surpassing ChatGPT on Apple’s App Store, with forecasts suggesting it could reach 100 million users within the next six to twelve months.
Credit rating agency KBRA’s Andrew Giudici indicates that while higher interest rates may affect deal pricing, they are unlikely to dampen overall borrower demand for capital in AI infrastructure. The growth imperative and competitive pressure drive companies to continue large-scale debt issuance despite cost headwinds.
Takeaway: Rising U.S. Treasury yields near 5.17% are sharply increasing borrowing costs for AI firms, intensifying financial risks amid a multitrillion-dollar debt surge necessary to fuel AI infrastructure expansion through 2030.