The AI buildout has become the defining capital-spending story of this decade, with hyperscalers scaling data centers, chip supply chains expanding, and power and cooling projects breaking ground across regions.
Yet the Federal Reserve’s January meeting minutes quietly flagged a problem regulators can’t simply model away: a meaningful slice of this boom is being financed in “opaque private markets” that “warranted monitoring.”
That line reads less like a footnote and more like a structural blind spot in the most crowded investment narrative of the cycle.
What the Fed actually said
In its financial-stability discussion, the minutes noted “elevated equity market valuations,” a “high concentration of market values and activities in a small number of firms,” and “increased debt financing” tied to AI-related developments.
Then came the admission investors should not gloss over: “the financing of the AI-related infrastructure buildout in opaque private markets warranted monitoring.”
The same section also flagged “vulnerabilities associated with the private credit sector,” including links to other nonbank lenders such as insurance companies and banks’ exposure to the sector.
The Fed did not call this a bubble.
But it did connect the AI boom to familiar late-cycle warning lights: stretched valuations, crowded leadership, and more leverage being used to fund growth.
Also Read: Is inflation stirring again? FOMC minutes raise flags
Why is the opacity a problem
Opacity matters because private credit is not priced minute-by-minute like public bonds.
In simple terms, stress can build quietly when loans are negotiated privately, valued less frequently, and held in vehicles where outside investors have limited visibility.
The scale is also growing.
Ares Management has estimated that private credit firms could finance about $5.5 trillion of capital across debt and equity in global infrastructure, including AI-related projects, through 2035.
If that pool expands as projected, the “private” part is not a niche; it’s potentially a major funding channel for the AI supply chain.
There are also early signs that AI is creating winners and losers fast enough to matter for lenders.
UBS said it estimates 25–35% of private credit portfolios face elevated AI disruption risk, and it warned that this exposure has not been fully priced in.
In the same outlook, UBS projected defaults could rise by roughly 2% in 2026 as disruption and restructuring pressures build.
What happens if the bets go wrong
The minutes themselves present the optimistic case: more AI investment likely means “higher debt issuance going forward,” but “low debt loads at most technology firms” suggest the capacity to absorb it.
That is a reasonable point, as many large-cap tech balance sheets are still stronger than the typical leveraged borrower.
The bear case is that the financing chain matters as much as the borrower.
Reuters reported in November that a big-tech borrowing surge, alongside signs of strain in private credit, was already spooking bond-market lenders to top-rated companies, raising the risk that funding costs could move higher.
Moody’s Analytics chief economist Mark Zandi has also warned that borrowing by AI companies “should be on the radar screen as a mounting potential threat to the financial system and broader economy” if expectations are missed and assets reprice.
The Fed’s closing message is not panic; it is vigilance.
The minutes’ phrase “warranted monitoring” is a signal that officials are tracking whether AI’s financing plumbing is becoming a broader stability issue, not just an equity-market storyline.
The next scheduled FOMC meeting, March 17–18, will be the next checkpoint for whether this stays a watch item or turns into a clearer, more formal concern.
https://invezz.com/news/2026/02/18/fed-minutes-expose-a-blind-spot-at-the-heart-of-the-ai-boom/
