Bank of America has warned that the artificial intelligence investment boom could follow a familiar pattern seen in previous capital cycles, with intensifying competition, falling prices and excess capacity potentially leaving investors disappointed despite the technology’s long-term promise.
The warning comes as billions of dollars continue to flow into AI infrastructure, including data centers, advanced chips and computing capacity. The scale of investment has made AI one of the biggest bets in US industrial history, but questions are mounting over whether companies will generate sufficient returns to justify the spending.
Railways, telecommunications and the internet all created enormous economic value, but investors also lost money when capital flooded into projects whose returns failed to justify their costs.
AI-related stocks are already under pressure. The Philadelphia Semiconductor Index has declined for seven consecutive sessions, leaving it around 13% below its recent high.
Bank of America analyst Sebastian Raedler has cautioned that the industry’s rapid expansion could eventually undermine the profitability that initially attracted so much capital.
Bank of America flags capital cycle risks
Raedler said the AI industry could be repeating a pattern in which strong initial returns encourage companies to invest aggressively, eventually creating excess capacity and putting pressure on prices.
Expert View
“This monetization disappointment in the face of intense competition is precisely the failure mode seen in past capital cycles.”
Sebastian Raedler
“Most major capital cycles of the past have ended in disappointment, even though the underlying technology often lived up to expectations,” Raedler noted.
The concern is that a technology can transform industries and deliver substantial economic benefits without generating attractive returns for every company investing in it.
High profit margins in the early stages of an investment boom typically encourage more companies to enter the market and commit additional capital. As capacity expands and competition intensifies, businesses can lose pricing power, eroding the returns that made the investment attractive in the first place.
AI is already experiencing stronger competition at the model level, particularly from Chinese open-weight models. Average token prices have fallen around 50% since the summer, adding to concerns about whether AI developers can maintain the profitability needed to support their infrastructure spending.
Investors concerned over spending and returns
Interactive Brokers chief market analyst Steve Sosnick told Reuters that investors are increasingly questioning “the speed, the efficacy and the profitability of the rapid build-out in AI”.
Sosnick said a slowdown in data-center construction would eventually reduce demand for hardware, as customers would no longer be racing to buy equipment at almost any price.
Such a shift could affect chipmakers and other suppliers that have benefited from the surge in AI infrastructure investment. If companies scale back their construction plans, equipment purchases could weaken, particularly if falling AI prices make it more difficult to justify additional computing capacity.
As infrastructure spending continues, companies are under pressure to demonstrate that their AI products can generate enough revenue and cash flow to support the investments behind them.
Warsh offers an optimistic view
Despite the concerns over valuations and monetization, Federal Reserve Chair Kevin Warsh struck an optimistic tone about AI’s potential economic benefits on Friday.
“It’s obviously hitting the demand side of the economy before it’s going to hit the supply side of the economy,” Warsh said.
“We don’t know in the next 12 or 18 months its (AI) effect on employment, but if you believe like I believe, which is it will make economies and countries that put it to good use more productive, that it’s going to make it so that we will have more wealth, then that has to be a very good thing.”
Kevin Warsh
Warsh’s comments point to the potential for AI to improve productivity and generate broader economic gains as businesses adopt the technology.
However, the potential long-term benefits do not eliminate the financial risks associated with the current investment cycle.
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