JPMorgan has warned that companies can no longer secure financing simply by associating themselves with artificial intelligence. Lenders are increasingly assessing whether these businesses have sustainable operations, manageable debt levels, and a realistic path to generating cash.
“The AI label alone is no longer enough to reassure lenders. Companies must show that they can finance investment, service their debt and eventually turn spending into cash flow,” Justin Biemann, global investment strategist at J.P. Morgan Private Bank, wrote in an Oct. 23 report.
Elon Musk echoed similar concerns on Sunday, warning that debt financing is becoming more difficult for AI neocloud providers, whose businesses rely heavily on data centers.
The developments could have implications for cryptocurrency markets, where AI has helped fuel investor risk appetite. Bitcoin and Nvidia both reached lows within weeks of ChatGPT’s launch in late 2022 before embarking on significant rallies. If financial pressure spreads across the AI industry, crypto assets could also face renewed volatility.
Investors are increasingly questioning whether heavy AI spending will deliver the revenue and profits needed to justify current valuations. Since Oct. 6, the tech-focused Nasdaq has dropped 6.7%, falling from 31,360 to 29,263. AI-linked companies such as Nvidia and Oracle have underperformed the broader index.
Credit Markets Signal Rising AI Financing Risks
Concerns are also becoming visible in debt markets, where the cost of insuring against defaults on bonds issued by several AI-related companies has climbed to record levels.
Investors use credit default swaps (CDS) to protect against a borrower failing to meet its debt obligations. In exchange for an annual premium, the buyer receives compensation if a specified credit event occurs. The premium, measured in basis points, reflects the perceived risk of default. For example, a 100-basis-point spread costs $100,000 per year to insure $10 million in debt.
Morgan Stanley data shows that weekly CDS trading linked to bonds from Oracle, SpaceX, Alphabet, Amazon, Meta, Broadcom, and Nvidia averaged more than $9 billion in September. That compares with less than $2 billion per week in July, highlighting a sharp increase in activity.
Companies that depend heavily on borrowing to fund AI infrastructure appear particularly vulnerable.
Biemann described an unnamed AI infrastructure business carrying tens of billions of dollars in debt and other obligations. Its five-year CDS spread has risen to 1,100 basis points, pushing the annual cost of insuring $10 million of its debt above $1 million.
According to Biemann, spreads at that level imply a five-year default probability approaching or exceeding 50%, compared with less than 30% a year earlier.
JPMorgan Says AI Credit Warnings Are Not Predictions
Biemann pointed to Lehman Brothers as an example of how CDS pricing can reveal financial stress before a major collapse. The bank’s CDS spreads averaged below 100 basis points in the third quarter of 2007 before exceeding 1,400 basis points by mid-September 2008, when Lehman filed for bankruptcy and helped trigger a global financial crisis.
Still, he cautioned that rising CDS spreads should be treated as warning signals rather than precise predictions of when a company might fail.
Current trading in credit protection tied to major AI companies appears more consistent with investors hedging their portfolios than positioning for an immediate crisis, he added.
Large AI companies with strong cash flows pay around 50 to 120 basis points for five-year credit protection. Biemann said these levels remain more indicative of portfolio insurance costs than expectations of financial distress.
Meanwhile, CDS spreads for some established infrastructure borrowers have moved toward 300 basis points. Protection costs across the broader investment-grade market remain comparatively stable.
The central risk lies with businesses that need continued access to debt markets while maintaining high spending and generating relatively little cash flow. As lenders become more selective, AI companies may need to demonstrate stronger financial discipline and clearer paths to profitability to secure additional capital.
