Jeff Schmid, president of the Federal Reserve Bank of Kansas City, said in a speech this week that investments in artificial intelligence (AI) have grown large enough to warrant macroprudential attention. He asked whether the AI sector could become "too big to fail," a term famously used during the 2008 financial crisis to describe banks whose failure would have threatened the broader economy.
Why regulators are worried
Schmid’s concerns focus primarily on the scale of the industry and the tightly woven financing relationships among firms. He noted that major technology companies have committed roughly $2,400 billion in AI investments, a sum that far exceeds previous corporate investment cycles and leaves little room for error if demand falls short of expectations.
The source of financing also worries policymakers: much AI development is debt‑funded or supported through interlinked financing structures. The Bank for International Settlements (BIS) has warned that a collapse in AI markets could shake credit markets in a manner comparable to the 2008 crisis, because exposures and mutual funding chains could propagate shocks across the financial system.
Market signals: rising CDS prices
Investors are beginning to price in these risks. Coverage cited by Schmid points out that around $750 billion of AI‑related deals tied to Nvidia have pushed up the company’s credit default swap (CDS) spreads, indicating that even lenders to the industry’s strongest players perceive greater risk.
Similarities and differences with past bubbles
Certain indicators make the AI boom reminiscent of the dot‑com era: market concentration and valuation metrics in some cases exceed levels seen in the early 2000s. Yet a key distinction is that today’s market leaders are generally profitable, unlike many internet firms in 1999–2000. That creates a dilemma for the Federal Reserve: profits suggest a sturdier foundation than pure speculation, but the size of investments and their debt financing mean that even a fundamentally healthy sector could transmit financial shocks if sentiment changes abruptly.
Implications for monetary policy and supervision
Schmid said that growing AI investment could raise demand for energy, semiconductors and construction capacity, complicating assessments of inflationary pressures and monetary policymaking. He also noted that as financing shifts from corporate balance sheets to credit markets and private lenders, risks can migrate to financial institutions overseen by the Federal Reserve.
Concentration remains the principal danger
According to Schmid, the most tangible threat is concentration: a handful of giant firms account for a significant share of equity gains and capital allocation, so any serious trouble at one of them would extend beyond the technology sector. He did not predict a collapse, but emphasized that a regional Fed president’s role includes flagging potential systemic risks before they materialize.
The significance of the language
Using the phrase "too big to fail" in reference to AI signals, in Schmid’s view, that AI has moved beyond a purely technological or market narrative and become an issue that could affect the stability of the entire financial system.
