Fed Officials Clash Over AI Investment Risks as Spending Reaches $2.4 Trillion

Furious pace of AI investment on some Fed officials' radar now

Aug 6 (Reuters) - Federal Reserve officials are beginning to mull whether the frenzied investment driving the buildout of the artificial intelligence sector is getting out of hand and creating risks for the financial sector. For now, some of the officials who have tackled the subject call for vigilance, dashed with a sense that a financial crisis mirroring what happened 20 years ago with housing, and to a lesser degree, the dot-com shakeout before that, is probably not in the offing. Still, the scale of investment, the uncertain returns for an unproven technology, the rise of tricky financing structures and increased use of debt have moved AI finance onto central bankers' radar. "I don't see this as a bubble kind of situation," Federal Reserve Bank of New York President John Williams said in ⁠an interview, opens new tab with Reuters conducted on Friday. "What we're seeing is a very high level of excitement, enthusiasm around new technology, around AI," Williams said. "Investors are trying in real time to solve an almost intractable problem, and that is how big are the benefits of AI going to prove to be," and trying to answer these questions will lead to volatility. Williams said that while there's been an increase in borrowing to support the AI investment it is being managed by companies with high earnings, noting, "I'm not as worried about the financial stability from the leverage right now." Torsten Slok, chief economist at money manager Apollo, said in a research note, "The data-center buildout is still less than half the size of the housing boom, which peaked at 6.6% of GDP in 2005," while at the same time the investment pace relative to GDP has been growing faster than housing did in the run up to the ⁠global financial crisis. MONITORING TIME Others on the Fed appear less sanguine about AI risk relative to Williams. Given how the industry is financing itself "I would argue that, that there's some signs that we have to really start to talk about that on a macro level, is this industry becoming another too big to fail?" asked Kansas City Fed President Jeff Schmid in a speech on Tuesday. In particular, he's worried about the flow of financing and how the linkages could be a vector where a problem ⁠starts at one stage and then propagates. Schmid asked, "Does the does the circular motion of a commitment, let's say a contractual commitment to a data center to an energy provider ... to a community that it serves, is that, is that circle getting too leveraged? And if you get a spark that starts a flame, what happens?" San ⁠Francisco Fed chief Mary Daly said on Wednesday, "If you just looked at the growth rate and the amount" of investment in the AI space, you could easily say this is "very worrisome." Offsetting that anxiety, Daly noted that it's key that many commitments being made in the AI space are currently announcements ⁠that haven't turned into physical realities, reducing the risk of so-called "stranded assets" that are hard to deal with after a shakeout. That said, the increased rise of borrowing to fuel growth might be an issue, Daly said. For the Fed, "It's really about putting a dashboard together, not of the things that happened in the financial crisis, but what could go wrong that would tip this over." Reporting by Michael S. Derby; Our Standards: The Thomson Reuters Trust Principles., opens new tab

AI's costly buildout complicates the Fed's inflation fight

The mismatch creates a challenge for Fed Chair Kevin Warsh as officials debate whether AI is the kind of inflation that requires interest rate hikes. Silicon Valley leaders from Elon Musk to OpenAI CEO Sam Altman have hyped the deflationary effects of the artificial intelligence boom. "Intelligence too cheap to meter is well within grasp," Altman wrote recently. Musk, the CEO of Tesla and SpaceX and the world's richest person, has argued that AI and robotics will create extreme abundance and drive down cost. SoftBank's Masayoshi Son said he expected a 40% drop in prices and that "unnecessarily hard work, sweating work, would no longer be needed." None of those dreams are close to being realized. Instead, AI is hitting a wall of corporate inertia as it spreads out into the economy -- causing some near-term inflation and producing little evidence of a sustained productivity boom. Company adoption has proved slower than some of the boosters promised. Meanwhile, the tech industry's multi-trillion-dollar spending spree on data centers and AI infrastructure has snarled supply chains. Spending to build out AI is raising prices in sectors like electricity. Costs are piling up before the full-scale payoff arrives. That poses a dilemma for the Federal Reserve, which needs to make decisions about how to manage inflation. Some of the immediate costs of AI are easier to spot than the potential benefits, said Ronnie Chatterji, chief economist for OpenAI. "For it to impact the economy, it has to be adopted by organizations," Chatterji said. "Those organizations have to realize value." While that is happening, Chatterji acknowledged that "it'll still be a little while before we see it sort of clearly for productivity statistics." Capital expenditure on the AI buildout is expected to reach $581 billion this year in the U.S., and as much as $1 trillion globally, Goldman Sachs Research recently estimated. Spending in the U.S. alone amounts to 1.8% of gross domestic product, a share the firm estimates will rise to 2.8% by 2028. A survey by the Census Bureau published in May found that between 17% and 20% of U.S. businesses reported using AI, which is far more prevalent at large firms than small ones. Peter Boockvar of One Point BFG Wealth Partners compared AI to the last major tech-driven productivity boom: the internet. Even during that period of automation, the U.S. saw only a 1.5% gain in productivity over a 30-year period, Boockvar said. If you zoom out 50 years, productivity averaged 2.5%. "To think that generative AI is going to bring that level of enhancement to the economy, relative to the internet, is tough," Boockvar said. "Technology has always made people more productive. But is generative AI multiple step functions higher? We just don't know." Inside companies, some executives who have put AI into widespread use are cautioning that the industry's promises need to be taken with a grain of salt. "The reality is that the technology is there," said Julie Averill, Lululemon's former chief information officer, who oversaw AI adoption at the company. "The hype is around the ease of the technology in a large organization." Lululemon used AI to help executives predict where products would sell best. That was a lot more complicated than using a chatbot. "The things that have always made implementations in large companies difficult still exist, which is people," Averill said. "Getting people to change their behaviors, taking them along the journey with you, and getting them to trust the model, that's hard." Chatterji said he'd seen similar patterns in OpenAI's data. He said the power users of AI deploy it at eight times the rate of average companies, measured by tokens per user. The gap has grown from two times since OpenAI published a report on it three months ago. "It is growing incredibly fast in terms of the gap between the frontier firms and the typical firms," Chatterji said. "The companies that are reorganizing their workflows around it and changing the way they work around AI, they're having more success." Economists who study AI have a term for what Averill experienced: weak links. That refers to tasks that can't be easily automated. AI makes us more productive by automating work like reading a radiological scan -- something AI can do very well. But jobs are really bundles of tasks, some more amenable to automation than others, according to Stanford professor Charles Jones, a leading scholar of how AI will affect growth. He's now on leave at Anthropic. The Nobel laureate technologist Geoffrey Hinton predicted in 2016 that radiologists wouldn't be needed within five to 10 years. Instead, their numbers kept growing as AI made radiologists more valuable to the economy. "It turns out that radiologists do more than just read scans, and AI tools complement those other skills by automating a fraction of the tasks that radiologists perform," Jones writes. The other things radiologists do -- talking to patients and working with colleagues, for instance -- fall in the category of weak links. The pervasiveness of weak links won't be clear until companies adopt AI at a bigger scale. Last month, Fed Chairman Kevin Warsh appointed Jones to a task force that will inform how the Fed thinks about AI and its effect on the economy. Venture capitalist Marc Andreessen, whose firm is aggressively backing AI startups, is also on the team, and is among those predicting an era of "hyper-deflation." When Jones, Andreessen and others report back in a few months, they will join a roiling debate at the Fed about AI. The Fed needs to raise its growth forecasts to account for AI, Warsh wrote in November, before he was confirmed to the top job. "AI will be a significant disinflationary force, increasing productivity and bolstering American competitiveness," he wrote. It's a position that helped his standing with President Donald Trump, who is lobbying for lower interest rates. Warsh's new colleagues aren't convinced. Fed officials voted in July to leave interest rates unchanged at a range of between 3.5% and 3.75%. The decision wasn't unanimous, as some Fed officials worried openly that they needed to restrain the economy to hold back AI-driven price increases. "The massive investment in data centers has also added a new demand element to the high inflation Americans are experiencing," Minneapolis Fed President Neel Kashkari said in a statement explaining his decision to dissent in favor of a higher interest rate. The rush to build power-hungry data centers is contributing to rising utility bills for many Americans. Household electricity prices rose 10.1% in the two years leading up to June. That was faster than the overall 6.3% increase in prices in that period, according to consumer price index data from the Bureau of Labor Statistics. Other Fed officials have raised concerns about supply chain constraints for the servers needed to power advanced models, as AI companies buy up all the chips they can from companies like Nvidia. Chipmakers haven't been able to ramp up production fast enough to meet demand. Prices on certain products have shot up. The cost of dynamic random access memory, or DRAM, will have risen by 400% by the end of the year compared to 2024, JPMorgan Chase estimates. CPI data shows the cost of computer software and accessories has risen 22.9% since June 2024, including 17.4% in the past year. That's prompted Warsh to adopt a newly cautious tone. Companies' vast AI spending is laying the groundwork for future growth, the Fed chairman said in July. But for now "the precise timing and magnitude of effects on the supply side remain hard to predict." "The cost and inflationary aspect is really complicating Kevin Warsh's job," Boockvar said. "He wants to believe in the productivity enhancements down the road -- but it's not something he can react to." In other words, AI may eventually live up to the hype. But for now, the costs are very real. -- CNBC'S Drew Troast contributed reporting. Choose CNBC as your preferred source on Google and never miss a moment from the most trusted name in business news.

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

From 'not a bubble' to 'very worrisome,' Federal Reserve officials are split on the furious pace of AI investment now shaping US growth, inflation and interest rates. 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.

Fed's Schmid says finances around AI buildout merit watching

Aug 4 (Reuters) - Federal Reserve Bank of Kansas City President Jeff Schmid said on Tuesday the financial situation involved in building out the artificial intelligence sector bears watching. "We have to ⁠correlate what's happening in AI, just from a pure scale standpoint, to some of the other experiences we've had that could, in fact, create a systemic problem," ⁠Schmid said at a conference at his bank. "I would argue that there's some signs...that ⁠we have to really start to talk about that on ⁠a macro level...is this industry becoming another too ⁠big to fail?," he added. Reporting by Michael S. Derby; Editing by Jacqueline Wong Our Standards: The Thomson Reuters Trust Principles., opens new tab

A Fed official is asking whether AI is becoming 'too big to fail'

Kansas City Fed president Jeff Schmid says the scale of AI investment now warrants watching at a macro level, borrowing a phrase last heard in the 2008 crisis. A senior Federal Reserve official has put an uncomfortable question on the table. Speaking this week, Kansas City Fed president Jeff Schmid said the finances around the AI buildout now merit close watching. Jeff Schmid said there were signs the industry had grown large enough that policymakers should start discussing it at a macro level, and asked whether AI was becoming another sector that was too big to fail. That phrase carries weight. It was the language of the 2008 financial crisis, when banks had grown so central that governments felt forced to rescue them, and hearing it applied to AI is a notable escalation in official tone. Schmid's worry is about scale and correlation. He suggested the current wave of AI spending should be compared with earlier booms, warning that concentration on this scale can turn a single sector's troubles into an economy-wide problem. The numbers behind the anxiety are staggering. Big Tech is now carrying nearly $2.4 trillion in AI spending commitments, a figure that dwarfs most previous corporate investment cycles and leaves little slack if demand disappoints. It is not only the amount but how it is financed. The Bank for International Settlements has warned that an AI bust could hit credit markets as hard as 2008, precisely because so much of the buildout runs through debt and circular deals. Those interlocking arrangements are what unsettle regulators. When chipmakers, cloud providers and model developers invest in one another, a stumble at any one node can ripple outward, and the exposure is harder to see from the outside. Markets have started to notice. Nvidia's wave of $750bn in AI deals pushed its credit default swaps to record levels, a sign that even lenders to the sector's strongest name are pricing in more risk. The comparison to past bubbles is not exact. On some measures the AI boom looks like the dot-com era, with valuations and concentration above 2000 levels, though the leading companies today are genuinely profitable in a way many 1999 darlings were not. That is the knot facing the Fed. Real earnings make the boom look sturdier than a mania, yet the spending is so large and so leveraged that even a healthy sector could transmit shocks if sentiment turns. Schmid's comments also touch monetary policy. If AI investment keeps driving demand for power, chips and construction, it complicates the central bank's reading of inflation and its decisions on interest rates. The spending is also straining the companies themselves. Big Tech's AI outlays are now catching up with its free cash flow, forcing firms that once funded everything internally to lean harder on debt and outside capital. That shift is what pulls the Fed into the story. As financing moves from corporate balance sheets into credit markets and private lenders, the risk spreads to institutions the central bank is charged with watching. Schmid is not alone in his unease. A growing chorus of officials and analysts has begun comparing the AI cycle to past manias, even as few are willing to call the top of a boom that keeps producing real revenue. The practical worry is concentration. A handful of enormous firms now account for a large share of market gains and capital spending, so a stumble by any one of them would be felt far beyond the technology sector. None of this amounts to a prediction of collapse. A Fed president musing about systemic risk is doing his job, and flagging a concern early is meant to prevent trouble rather than forecast it. But the vocabulary matters. Once officials reach for the language of too big to fail, they are signalling that AI has moved from a market story to a question about the stability of the whole system.

Fed officials watch AI investment surge for financial risks By Investing.com

Investing.com -- Federal Reserve officials are monitoring whether the rapid investment in artificial intelligence infrastructure poses risks to the financial sector. Some Fed officials have called for careful observation but say a financial crisis similar to the housing collapse or dot-com bust appears unlikely. The large scale of investment, uncertain returns from unproven technology, complex financing structures and increased debt use have drawn central bankers' attention. "I don't see this as a bubble kind of situation," Federal Reserve Bank of New York President John Williams said in an interview conducted on Friday. Williams noted high levels of excitement around new technology and AI. "Investors are trying in real time to solve an almost intractable problem, and that is how big are the benefits of AI going to prove to be," he said, adding that attempts to answer these questions will lead to volatility. While borrowing to support AI investment has increased, Williams said it is being managed by companies with high earnings. "I'm not as worried about the financial stability from the leverage right now," he stated. Kansas City Fed President Jeff Schmid expressed more concern in a speech on Tuesday. Given how the industry finances itself, "I would argue that, that there's some signs that we have to really start to talk about that on a macro level, is this industry becoming another too big to fail?" Schmid asked. This article was generated with the support of AI and reviewed by an editor. For more information see our T&C.