As tech giants ramp up debt issuance to fund AI infrastructure, investors are growing increasingly concerned about potential credit risks.

According to the latest data from clearinghouse DTCC, credit default swap (CDS) trading volumes linked to a handful of U.S. tech conglomerates have surged 90% since early September. CDS, an insurance-like financial instrument, provides protection to investors in case of corporate defaults.

This hedging frenzy coincides with renewed Wall Street sell-offs in tech stocks, driven by disappointing earnings from companies like Oracle and Broadcom that fell short of lofty investor expectations.

Investor unease stems from a wave of debt-fueled AI infrastructure spending by tech firms. These capital-intensive projects, which may take years to generate returns, are prompting market participants to reassess credit risks and actively seek protective strategies.

**AI Funding Shift Turns Credit Markets into New Battleground** Earlier this year, credit risk was virtually a non-issue for high-rated U.S. tech companies, which primarily relied on massive cash reserves and robust profitability to fund AI initiatives. However, soaring costs have changed the equation.

This fall alone, Meta, Amazon, Alphabet, and Oracle have collectively raised $88 billion through bond sales specifically earmarked for AI projects. JPMorgan predicts investment-grade firms may need to raise $1.5 trillion for AI financing by 2030. This shift from internal funding to public debt has exposed tech companies' credit profiles to heightened market scrutiny.

"Sentiment has shifted from viewing these firms as nearly risk-free to recognizing certain companies carry risks that warrant hedging," noted an asset manager. This shift became evident when a new Meta CDS market emerged shortly after the company's $30 billion AI bond offering in October.

**CDS Trading Surges with "Hyperscalers" in Focus** As tech firms increasingly tap debt markets, single-name CDS—particularly for individual companies—has seen notable growth.

JPMorgan credit strategist Nathaniel Rosenbaum observed: "Single-name CDS volumes have risen sharply this quarter, especially among hyperscale companies building massive data centers nationwide."

A senior executive at a major credit investment firm confirmed the trend: "We're seeing significant upticks in single-name CDS trading, with growing use of baskets targeting big tech names or specific plays on Oracle and Meta." He added, "The most common hedge? Tech basket CDS."

The activity is particularly pronounced for Oracle and cloud firm CoreWeave, both financing billion-dollar data center expansions through debt.

**Oracle's Risk Profile Sparks Concern as Hedging Costs Hit 15-Year High** Among tech heavyweights, Oracle has become a focal point for investors. Its lower credit rating relative to investment-grade peers makes it more vulnerable to market volatility.

Data shows Oracle's weekly CDS trading volume has more than tripled this year, with protection costs soaring to levels last seen in 2009. The company recently missed Q3 revenue estimates and delayed at least one data center project, triggering steep sell-offs in its equity and bonds.

Altana Wealth is betting against Oracle's credit via CDS. Portfolio manager Benedict Keim stated: "We don't expect imminent default, but Oracle's CDS is severely mispriced." Colleague Mathieu Scemama cited the company's rising debt load and reliance on single customer OpenAI as creating a "low-hanging opportunity."

**Investors Seek "Insurance" as Single-Name Hedging Gains Momentum** Current market dynamics suggest single-name CDS is entering an active phase. "Single-name CDS is having its moment," said Wellington portfolio manager Brij Khurana.

He explained that as banks and private credit firms accumulate larger exposures to individual companies, "they genuinely want to reduce that risk. People are buying insurance for their holdings."

Beyond default protection, CDS allows investors to hedge against or speculate on bond price fluctuations, providing flexible risk management tools during AI's uncertain investment cycle.