Massive Credit Fueling AI Boom as Debt Risks Rise

Credit is playing a central role in the explosive growth of artificial intelligence, with financial institutions and private lenders deploying tens of billions of dollars into AI infrastructure and development. JPMorgan Chase & Co. and Mitsubishi UFJ Financial Group are leading a $22 billion loan package to support Vantage Data Centers in constructing a large-scale data-center campus [5], while Meta Platforms Inc. has secured $29 billion in financing from Pacific Investment Management Co. and Blue Owl Capital for a major data center in rural Louisiana [1]. These transactions reflect a broader trend of credit-driven investment that is reshaping how AI is funded.

According to estimates from UBS, private credit funding for AI is running at a minimum of $50 billion per quarter, a figure that has remained stable across the past three quarters [1]. This surge is largely facilitated by bond investors and private credit lenders, who are increasingly stepping in as primary sources of capital for AI infrastructure. Much of the debt funding now is sourced from private credit markets, with commercial mortgage-backed securities (CMBS) tied to AI infrastructure seeing a 30% increase to $15.6 billion year-to-date [1].

However, the rapid buildup of AI infrastructure has sparked concerns about a potential bubble. OpenAI CEO Sam Altman has drawn comparisons between the current AI investment wave and the dot-com bubble of the late 1990s, warning that "someone’s gonna get burned there" [1]. A report from the Massachusetts Institute of Technology indicates that 95% of generative AI projects in the corporate world have failed to generate any profit, underscoring the uncertainty surrounding AI’s long-term value [1].

Industry experts have also raised alarms about the sustainability of these investments. Daniel Sorid of Citigroup noted that the AI boom brings to mind the telecom overbuilding of the early 2000s, which led to significant asset write-downs [1]. Ruth Yang of S&P Global Ratings highlighted the risk associated with 20- to 30-year funding deals for a technology whose future performance is still uncertain [1]. This uncertainty is further compounded by the fact that many AI-focused projects are being financed with long-term debt before they have proven their ability to generate consistent returns.

The shift toward debt financing has also introduced new financial risks. UBS Group noted a rise in payment-in-kind (PIK) loans among tech-oriented private credit lenders, with PIK income in business development companies (BDCs) reaching the highest level since 2020 in the second quarter, climbing to 6% [1]. These trends point to growing leverage in the sector, which could amplify the impact of a potential downturn.

Despite the risks, the flow of capital into AI shows no sign of slowing down. John Medina of Moody’s explained that direct lenders continue to raise capital and are eager to deploy it in large-scale AI infrastructure, which they view as the next long-term asset class [1]. The coming months will be crucial in determining whether this investment surge will lead to sustainable growth or set the stage for a correction.

Source:

[1] Fortune - [https://fortune.com/2025/08/24/private-credit-bonds-loans-debt-ai-boom-bubble/](https://fortune.com/2025/08/24/private-credit-bonds-loans-debt-ai-boom-bubble/)

[5] SwingTradeBot - [https://swingtradebot.com/news-articles/22077225-credit-fuels-ai-boom-fears-bubble](https://swingtradebot.com/news-articles/22077225-credit-fuels-ai-boom-fears-bubble)