Jim Covello, Goldman Sachs’s head of stock research, warned that building too much of what the world doesn’t need “typically ends badly.”
As Jim Covello’s car barreled up highway 101 from San Jose to San Francisco this month, he counted the billboards about artificial intelligence. The nearly 40 signs he passed, including one that promoted something called Writer Enterprise AI and another for Speech AI, were fresh evidence, he thought, of an economic bubble.
“Not that long ago, they were all crypto,” Mr. Covello said of the billboards. “And now they’re all A.I.”
Mr. Covello, the head of stock research at Goldman Sachs, has become Wall Street’s leading A.I. skeptic. Three months ago, he jolted markets with a research paper that challenged whether businesses would see a sufficient return on what by some estimates could be $1 trillion in A.I. spending in the coming years. He said that generative artificial intelligence, which can summarize text and write software code, makes so many mistakes that it was questionable whether it would ever reliably solve complex problems.
The Goldman paper landed days after a partner at Sequoia Capital, a venture firm, raised similar questions in a blog post about A.I. Their skepticism marked a turning point for A.I.-related stocks, leading to a reassessment of Wall Street’s hottest trade.
Goldman’s basket of A.I. stocks, which is managed by a separate arm of the firm and includes Nvidia, Microsoft, Apple, Alphabet, Amazon, Meta and Oracle, has declined 7 percent from its peak on July 10, as investors and business leaders debate whether A.I. can justify its staggering costs.
The pause has come early in the A.I. arms race. The tech industry has a history of spending big to deliver technology transitions, as it did during the personal computer and internet revolutions. Those build outs spanned five years or more before there was a reckoning.