Goldman Sachs says the return on investment for AI might be disappointing

Tech companies are spending big on the AI craze, but it will be a while before they have much — if anything — to show for it.

As companies prepare to spend over $1 trillion on artificial intelligence, a Goldman Sachs report examined the big question at hand: “Will this large spend ever pay off?”

That sizable investment will go toward the data centers needed to run AI, the power grid, and AI chips. But shortages of those AI ingredients could lead to disappointing returns for companies.

“AI technology is exceptionally expensive, and to justify those costs, the technology must be able to solve complex problems, which it isn’t designed to do,” Jim Covello, the head of Global Equity Research at Goldman Sachs, said in the report.

“The starting point for costs is also so high that even if costs decline, they would have to do so dramatically to make automating tasks with AI affordable,” he added. “In our experience, even basic summarization tasks often yield illegible and nonsensical results.”

He’s not wrong. Google scaled back its AI use in search after its bot began making some odd suggestions, including telling a Business Insider correspondent to put glue on their pizza to keep the cheese in place.

The tech industry is also “too complacent in its assumption that AI costs will decline substantially over time,” especially when that assumption seems to rely on competition dethroning Nvidia, which dominates the market with its AI chips, Covello said.

Other experts quoted by Goldman Sachs were more enthusiastic.

“AI technology is undoubtedly expensive today. And the human brain is 10,000x more effective per unit of power in performing cognitive tasks vs. generative AI,” said Kash Rangan, a senior equity research analyst at Goldman Sachs. “But the technology’s cost equation will change, just as it always has in the past.”

Eric Sheridan, another senior equity research analyst at the company, compared it to the tepid initial reactions to technological developments like the iPhone and Uber.

“People didn’t think they needed smartphones, Uber, or Airbnb before they existed. But today it seems unthinkable that people ever resisted such technological progress. And that will almost certainly prove true for generative AI technology as well,” Sheridan said.

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Katie Balevic