Private Credit Fuels AI, But Moody’s Sees a Debt Time Bomb Ahead

Moody’s Ratings warned Tuesday that the artificial intelligence boom is creating new opportunities for private credit lenders while increasing risks tied to the industry’s growing financing needs and interconnected relationships between technology companies.

Spending on AI infrastructure is extending beyond data centers to land, electricity access, semiconductors and specialized chips, including graphics processing units (GPUs) and tensor processing units (TPUs), Reuters reported, citing the Moody’s report.

Moody’s projected that combined capital spending by the five largest U.S. hyperscalers and CoreWeave (NASDAQ:CRWV) could approach $1 trillion in 2027, financed through a mix of internal cash flow, borrowing, joint ventures and special-purpose vehicles.

Expansion Comes With Credit Risks

Companies are taking on more debt to fund capital-intensive projects. Moody’s warned that a wave of loans coming due between 2027 and 2029 could make refinancing difficult for weaker borrowers if interest rates remain elevated.

About 17% of the 607 borrowers the agency tracks use payment-in-kind (PIK) interest, which lets companies defer cash interest payments by adding them to their outstanding debt. The arrangement can preserve cash in the short term but increases borrowers’ debt burdens over time.

A Reuters analysis earlier in 2026 found that maturities among U.S. business development companies were also expected to peak in 2028 and 2029. Meanwhile, stress in CoreWeave’s debt has highlighted investor concerns about heavily leveraged companies tied to the AI infrastructure boom.

Moody’s also raised concerns about the growing web of financial relationships between technology companies, chipmakers and AI developers. 

Through what the agency described as "circular" financing, companies increasingly invest in, lend to and purchase products or services from one another. Those connections could magnify losses during a downturn, leaving multiple companies exposed to the same financial pressures.

The risks come as AI infrastructure projects face additional challenges, including rising funding costs, construction delays and limited electricity supply. Such constraints could push back project timelines and increase capital requirements, complicating efforts to finance an expansion that has become central to the technology industry’s growth.

Image via Shutterstock/ Piotr Swat