Goldman Sachs is throwing cold water on the artificial intelligence industry, saying its ability to solve problems doesn’t justify its cost.

Companies large and small are investing billions in generative AI, with the financial firm saying those investments will top $1 trillion in the coming years. Despite the heavy cost, however, Goldman Sachs is warning in a report (via the Internet Archive)that “the technology isn’t designed to solve the complex problems that would justify the costs, which may not decline as many expect.”

Much of the issue stems from the high cost and the limited potential for AI to be capable enough to be cost-effective any time in the near future, as Goldman Sachs points out:

We first speak with Daron Acemoglu, Institute Professor at MIT, who’s skeptical. He estimates that only a quarter of AI- exposed tasks will be cost-effective to automate within the next 10 years, implying that AI will impact less than 5% of all tasks. And he doesn’t take much comfort from history that shows technologies improving and becoming less costly over time, arguing that AI model advances likely won’t occur nearly as quickly—or be nearly as impressive—as many believe. He also questions whether AI adoption will create new tasks and products, saying these impacts are “not a law of nature.” So, he forecasts AI will increase US productivity by only 0.5% and GDP growth by only 0.9% cumulatively over the next decade.

GS Head of Global Equity Research Jim Covello was even more pessimistic, contrasting AI’s high cost to other industry-disrupting technologies that started out far more cost-effective:

Many people attempt to compare AI today to the early days of the internet. But even in its infancy, the internet was a low-cost technology solution that enabled e-commerce to replace costly incumbent solutions. Amazon could sell books at a lower cost than Barnes & Noble because it didn’t have to maintain costly brick-and-mortar locations. Fast forward three decades, and Web 2.0 is still providing cheaper solutions that are disrupting more expensive solutions, such as Uber displacing limousine services. While the question of whether AI technology will ever deliver on the promise many people are excited about today is certainly debatable, the less debatable point is that 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.

Covello goes on to tell Goldman Sachs that he’s skeptical that AI can achieve the transformative effect that the internet, cell phones, and laptops have achieved.

More broadly, people generally substantially overestimate what the technology is capable of today. In our experience, even basic summarization tasks often yield illegible and nonsensical results. This is not a matter of just some tweaks being required here and there; despite its expensive price tag, the technology is nowhere near where it needs to be in order to be useful for even such basic tasks. And I struggle to believe that the technology will ever achieve the cognitive reasoning required to substantially augment or replace human interactions. Humans add the most value to complex tasks by identifying and understanding outliers and nuance in a way that it is difficult to imagine a model trained on historical data would ever be able to do.

Others—such as GS senior global economist Joseph Briggs and internet analyst Eric Sheridan—were slightly more optimistic. Briggs sees AI automating as much as 25% of work in the next decade, and raising US productivity by 9% and GDP by 6.1%.

Ultimately, it may be the industries that support AI to be the ones that most benefit from it before a potential bust, according to Goldman Sachs:

Although Covello believes AI’s fundamental story is unlikely to hold up, he cautions that the AI bubble could take a long time to burst, with the “picks and shovels” AI infrastructure providers continuing to benefit in the meantime. GS senior US equity strategist Ryan Hammond also sees more room for the AI theme to run and expects AI beneficiaries to broaden out beyond just Nvidia, and particularly to what looks set to be the next big winner: Utilities.

That said, looking at the bigger picture, GS senior multi-asset strategist Christian Mueller-Glissmann finds that only the most favorable AI scenario, in which AI significantly boosts trend growth and corporate profitability without raising inflation, would result in above-average long-term S&P 500 returns, making AI’s ability to deliver on its oft-touted potential even more crucial.

Goldman Sach’s full report is well worth a read and illustrates in detail the challenges facing the AI industry. As the report highlights, companies will need to demonstrate that AI can deliver on its promise if the vast investments are to be justified. Otherwise utilities and chip companies may be the only industries to see a return that’s worth it.