Wall Street skeptic throws cold water on the rise of artificial intelligence: is it pure hype?

As Jim Covello, head of equity research at Goldman Sachs, drove down Highway 101 this month, billboards screaming about artificial intelligence only reinforced his suspicions. From “Writer Enterprise AI” to “Speech AI,” these signs looked eerily similar to the pre-crisis cryptocurrency craze.

Covello has become a leading voice of caution on Wall Street about AI. His research paper, which questions the return on investment for the projected $1 trillion in AI spending, has sent shockwaves through the market. He argues that current generative AI, which can summarize text and write code, is prone to errors, raising questions about its ability to tackle complex problems reliably.

The skepticism comes at a crucial moment in the AI ​​arms race. The tech industry has a history of spending heavily during technological transitions, such as the PC and Internet revolutions. But Covello, a veteran of the dot-com bubble bust, worries about the potential for another bust. He recalls the human cost of that period, with colleagues losing their jobs due to overinvestment.

Internally at Goldman Sachs, Covello has looked at various AI services. He found them expensive, cumbersome, and lacking the intelligence needed to truly empower employees. That experience fuels his belief that the current boom may be overhyped.

Not everyone shares his pessimism, however. George Lee, co-head of Goldman’s geopolitical advisory business, sees AI as a tool to increase worker productivity and urges patience for further refinement. This internal debate highlights the need for a nuanced perspective on AI’s potential.

Covello’s skepticism may seem like a lone voice amid the AI ​​hype, but it’s sparking crucial conversations. Firms are reassessing their investments, and Goldman Sachs itself has begun hosting bull and bear debates with Covello and Lee.

While Covello predicts a slowdown as companies tighten their belts, he acknowledges the possibility of being wrong. He actively seeks out his potential blind spots, a testament to his commitment to a balanced view of this transformative technology.

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