AI boom raises ‘too-big-to-fail’ concerns as ecosystem expands, says Kansas Fed's Jeff Schmid

Kansas City Federal Reserve President Jeff Schmid has raised concerns about whether the rapid expansion of the artificial intelligence industry and data-centre investment could eventually create an ecosystem so interconnected and economically significant that it becomes “too big to fail.”

Speaking about the AI boom, Schmid said the Federal Reserve needs to better understand the network of companies, financing arrangements and contracts developing around the technology as investment accelerates.

"Where we have to start to really synthesize what's happening in the AI and the data center build-out is are we moving to a too-big-to-fail AI ecosystem," he said, according to a Reuters report.


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Schmid’s comments draw a parallel with the financial system before the 2008 crisis, when large banks and financial institutions had become deeply interconnected through lending, securities and complex financial contracts. When losses linked to the US housing and mortgage markets spread through the system, the failure or distress of major institutions threatened broader financial stability.

The crisis intensified in 2008 after the collapse of Lehman Brothers, while the US government and Federal Reserve took extraordinary measures to stabilise financial institutions and credit markets. The episode demonstrated how institutions considered systemically important could create significant risks for the wider economy when their problems spread through interconnected financial networks.

Schmid said the question for policymakers is whether a similar dynamic could emerge around AI, particularly as technology companies, semiconductor firms, cloud providers, data-centre operators, energy companies and financial institutions become increasingly linked through investment and commercial contracts.

"You worry a little bit about how do we understand what's inside. ... Is there anything systemic?" he asked.

How the AI ecosystem compares with 2008 financial crisis

Schmid’s comments point to a potential policy challenge: understanding whether the concentration of capital, infrastructure and business relationships could create risks that extend beyond individual companies.

Before the 2008 crisis, risks were difficult to assess because financial institutions were connected through mortgage-backed securities, derivatives, short-term funding and other contractual relationships. Problems in one part of the system could therefore transmit losses to other institutions.

The emerging AI ecosystem's connections are largely based on technology supply chains, capital expenditure, computing capacity, cloud infrastructure, semiconductor supply, power requirements and long-term commercial agreements. The scale of investment in data centres also means that AI development increasingly intersects with real estate, utilities, construction, energy and financing.

For the Fed, the challenge is therefore not simply tracking the valuation of AI companies. It is understanding what lies beneath the boom and whether financial or economic linkages are becoming sufficiently concentrated or interconnected to pose systemic risks.

Schmid’s remarks underscore why the rapid build-out of AI infrastructure is attracting increasing attention from central bankers. As investment grows, policymakers may need greater visibility into the financing structures and contractual relationships supporting the ecosystem to determine whether vulnerabilities are building beneath the technology boom.

(Disclaimer: This article is based on inputs from agencies. These do not represent the views of The Economic Times)