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The AI Industry’s Profit Problem Is Getting Bigger, Goldman Sachs Says

AI has improved rapidly and drawn massive investment, but the business case remains unproven, according to Goldman Sachs’ Jim Covello.

“We’ve gotten further away from that over the last couple years instead of closer to it,” Covello, the bank’s head of global equity research, said on the “Exchanges” podcast published on Tuesday.

That’s because as companies continue to invest, the amount of profit needed to justify those expenditures is also increasing, he said.

Covello’s comments come as companies pour hundreds of billions into AI and the S&P 500 reaches fresh record highs, even as investors continue to debate whether the technology will generate returns that justify the spending.

He acknowledged that several developments have exceeded his expectations: Consumer adoption has been stronger than anticipated, AI models have advanced quickly, and companies continue to increase spending on the technology.

It’s still unclear whether AI can deliver returns that justify the enormous spending.

“All of the economic value has continued to accrue to the semiconductor companies,” Covello said.

That contrasts with previous technology cycles, when chipmakers prospered when their customers prospered.

Now, semiconductor companies have captured outsized profits, while companies above them in the AI supply chain have yet to show comparable economic returns, Covello said.

Major cloud providers have continued ramping up AI-related capital expenditures, even as investors debate when those investments will begin generating meaningful returns.

“In a lot of ways, companies are losing more money today implementing this technology than they were two years ago,” he said.

A big reason is fear of being left behind.

“There is a tremendous amount of FOMO at every level of the supply chain,” Covello said, adding that spending has outpaced proven returns.

“I think it’s because everybody is afraid of what happens if the technology really takes off and finds significant positive economic use cases, and your competitors have that figured out and you don’t,” he said.

Ultimately, the question is whether the industry’s massive AI spending will deliver a meaningful payoff.

“At some point, you got to make money. You make investments in a business so that you can generate returns and make money,” he said.

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