The Fed can’t agree on how worried to be about the AI boom

The AI spending boom has grown large enough that the Federal Reserve can no longer ignore it, and the furious pace of investment is now firmly on the radar of several central-bank officials.

What they cannot agree on is how alarmed to be, because their public comments range from relaxed to distinctly uneasy, a spread that captures just how hard the boom is to read.

At the calm end sits New York Fed President John Williams, who said he does not see this as a bubble and that he is not especially worried about financial stability from leverage right now.

His reasoning rests on who is borrowing, since much of the spending is being done by highly profitable companies that can absorb the debt far more comfortably than weaker borrowers could.

Others are far less sanguine. San Francisco Fed chief Mary Daly called the sheer growth rate and scale of the investment potentially very worrisome, a notably sharper choice of words, and she flagged a credibility gap too: many of the eye-catching AI commitments remain announcements rather than completed projects, which makes the real level of spending hard to gauge.

Kansas City’s Jeff Schmid has gone furthest of all, questioning whether AI is becoming another sector that is simply too big to fail, unsettled by the circular financing that links data centres, energy providers, and their backers into a single web of mutual dependence.

Behind the debate is a genuine macro shift, because AI capital spending has become a meaningful driver of US growth in its own right, which means a sudden slowdown could weigh on the whole economy and not just on tech stocks. One comparison helps size it up.

Apollo’s Torsten Slok likened the build-out to the housing boom, noting that data-centre investment is still less than half the size housing reached at its 2005 peak of 6.6% of GDP.

The pace, though, is the worry: by Slok’s reckoning AI investment is accelerating faster than housing did before the 2008 crash, which is exactly the sort of trajectory that makes central bankers nervous.

The scale of the commitments is staggering, with Big Tech now carrying nearly $2.4 trillion in AI spending pledges, a figure that dwarfs most previous investment cycles.

What regulators watch most closely, though, is the financing, and the Bank for International Settlements has warned that an AI bust could hit credit markets as hard as 2008, precisely because so much of it runs through debt and interlocking deals.

The bubble question, meanwhile, refuses to settle. On some measures the boom echoes the dot-com era, though today’s leaders are genuinely profitable in a way many of 1999’s were not.

The pressure is even reshaping the balance sheets of the giants, and companies like Meta are lifting capital spending even as cash flow tightens, the kind of stretch that turns a corporate story into a macro one.

For policy, the growth question cuts both ways. If AI spending is doing much of the heavy lifting in the economy, then a stumble would slow growth just as the Fed is trying to judge how far to cut rates.

Inflation is the mirror-image risk, since the build-out is pushing up demand for power, construction, and skilled labour, pressures that could keep prices higher than the Fed would like even as the technology promises long-run efficiency.

The jobs picture is murkier still, because AI is credited with both creating demand for infrastructure work and threatening to displace white-collar roles, which leaves officials unsure which effect will dominate.

Viewed that way, the dilemma facing the central bank is a genuinely difficult one. The Fed must weigh a transformative technology that is currently propping up growth against the risk that a debt-fuelled boom, if it eventually turns, complicates everything from inflation to interest rates in one go.