Artificial Intelligence on the “Credit Needle”: How Private Debt is Fueling the AI Boom—and Where It Might Crack

The boom in borrowed computing

Artificial intelligence is growing, but increasingly on borrowed money . Leading players in the industry, in addition to venture capital and equities, are increasingly turning to private credit (direct lending from non-bank funds) to finance data centers, GPU clusters, and long experimental cycles. Experts warn that the sector is accumulating a “credit card,” where interest is real but profits are not yet. This is how Futurism’s review of the AI industry’s “debt problem” characterizes the situation, based on market assessments and investment bankers’ comments.

What is a private loan - in simple words

Private credit (private credit, private debt) is non-public loans from non-bank lenders (private debt funds, BDCs, etc.) directly to companies; the terms are more flexible than those of banks or public bonds, but more expensive in terms of rate and covenants. According to the US Federal Reserve researchers, this is one of the fastest growing segments of non-bank financing; the volume in the US alone is estimated at over a trillion dollars.

Why is Artificial Intelligence “drawn” to private debt?

• High capex : data centers, energy, GPUs — the bill is in the billions, and the profits are deferred over time. Cheap money is running out, so private debt is filling the gap.

• Speed and customization : Private deals close faster than public markets, with terms tailored to the specific project.

• The scale of the wave : According to business media reports, AI financing through private credit is already measured in the tens of billions per quarter , with banks and funds warning of the risk of “overheating.”

The "Credit Card" of Industry: Where It's Fine

Even without the stock market’s “advertising algorithms,” the AI debt engine is revving. Analysts are comparing the situation to the telecom boom of the 2000s: infrastructure can be “rebuilt,” and debt can be “recycled.” It is this historical parallelism that credit strategists at major investment banks are voicing.

A separate signal is PIK interest (interest accrual on debt) and "soft defaults": extensions, vacations, conversions, which are not always visible in the usual metrics. The 2024–2025 private credit reports warn: nominally low defaults can mask real portfolio stress.

Market surveys also record: warnings about the growth of delinquencies in private credit are multiplying; the inclusion of "non-accrual" loans significantly increases the assessment of defaults compared to official indicators.

Is it a bubble? Signs of overheating

Large banks are openly writing about the risk of AI lending overheating , and private debt volumes have “gone” far beyond small and medium-sized businesses — towards large tech companies and infrastructure deals . At the same time, some experts point out that monetization lags behind investment — many AI projects are still “far from profitable,” which increases sensitivity to recession and interest rates.

But not everything is so gloomy: why does this market exist?

Leading investors see private credit as a functional bridge between venture capital and public markets: when companies are not yet ready for an IPO and need to scale “yesterday.” With smart risk management, the class is capable of providing a yield premium and financing real innovations.

What does this mean for Ukraine?

• For AI startup founders : private credit can be a tool for equipment/data centers, but only with proven cash flow and clear covenants . Calculate runway , DSCR/ICR , PIK potential, and stress scenarios (revenue delay, margin decline). Overestimation of demand for inference is the main risk. (Analytical recommendation of the Academy)

• Investors : demand transparent covenants , quarterly PIK/rollover disclosure, check collateral structure (computing assets, long-term capacity contracts). Compare the real CAC/LTV of models with the rate of increase in GPU and electricity prices. (Academy analytical recommendation)

• To the state and regulators : stimulate energy-efficient data centers , public R&D co-financing programs, and disclosure standards for private debt — to avoid “invisible risk” in the financial system. (Analytical recommendation of the Academy)

Healthy Debt Checklist for AI Companies

• Unit economics : positive gross margin after infrastructure costs.

• Contracts : long-term capacity/customer agreements with minimal termination penalties.

• Covenants : net debt limits, PIK threshold, minimum cash buffer (3–6 months).

• Risk portfolio : scenarios >12 months without new capital; CAPEX→OPEX plan.

• Reporting : Show cash payments vs. PIK accruals separately.

Academy Conclusion

The AI revolution will not stop — but financial architecture matters. Today, the AI industry is on a fine line between acceleration and overheating : private credit has given speed, but requires discipline. If you are building an AI business, also build an anti-fragile financial model . If you are an investor, demand honest risk disclosure . Otherwise, the “AI credit card” may charge interest that the industry finds painful to pay.

Sources for a deeper dive

• Futurism : On the AI industry's "debt problem" and quotes from credit strategists.Futurism

• UBS/Bloomberg : Warning of overheating private credit in tech. Bloomberg

• US Federal Reserve / Boston Fed : what is private credit and why is it growing rapidly. Federal Reserve System Federal Reserve Bank of Boston

• FT / Bloomberg : PIK-income risks and hidden defaults in BDC/private debt; signals of stress. Financial Times Bloomberg

• JPMorgan / Wellington : When Private Credit Works and Key Trends 2025. JPMorgan Wellington