Goldman Sachs Warns AI Earnings Boom Is Losing Steam as S&P 500 Faces 2027...

Wall Street's enthusiasm over strong corporate earnings and the AI investment boom may face a tougher test next year, as Goldman Sachs warns that the forces responsible for a large share of the S&P 500's earnings growth in 2026 are unlikely to provide the same lift in 2027.

Ben Snider, Goldman's chief U.S. equity strategist, said the artificial intelligence investment boom has accounted for nearly half of S&P 500 earnings growth this year. But even if companies continue spending heavily on data centers, chips, and other AI infrastructure, that spending may no longer generate the same earnings momentum.

"The AI investment boom has accounted for nearly half of S&P 500 earnings growth this year, and this tailwind should begin to fade next year even as capex spending continues to grow," Snider wrote in a note to investors on Thursday.

Goldman is understood to not be making the case that the AI trade is about to collapse. Instead, the bank's base case is that the earnings growth supporting the broader U.S. stock market could slow significantly over the next two years as some of the biggest beneficiaries of AI spending encounter tougher comparisons and weaker profit-margin expansion.

That creates a different risk for the market. The problem may not be that technology companies suddenly stop investing in AI, but that continued investment produces diminishing incremental earnings growth for the companies supplying the infrastructure.

Semiconductor Profits Become a Key Vulnerability

Chipmakers have been among the biggest beneficiaries of the AI boom since late 2022. Demand for advanced processors and related infrastructure has surged as technology companies build increasingly large data centers to train and operate AI models.

Limited supply has allowed semiconductor companies to command high prices and expand margins, creating an unusually powerful earnings tailwind for the broader market.

Goldman now expects that effect to weaken.

"The recent surge in semiconductor profit margins leaves S&P 500 earnings vulnerable to a decline in chip prices," Snider said. "Our industry analysts expect supply to remain tight through 2027 but for the rate of margin expansion to slow next year."

But that does not require a collapse in AI demand.

If chip supply increases while demand continues to grow, prices can still come under pressure because semiconductor producers would have less pricing power. The resulting moderation in margins could therefore slow earnings growth even while AI infrastructure investment remains historically high.

That is one of the more important distinctions in Goldman's outlook. Investors have increasingly treated rising AI capital expenditure as evidence that the semiconductor earnings cycle can continue accelerating. Goldman is warning that the relationship between spending and profits may weaken.

"In a scenario where slowing AI infrastructure investment, increasing supply, and/or technological shift lowers semiconductor prices and profit margins, S&P 500 EPS growth would also disappoint," Snider wrote.

For a market that has become more dependent on a relatively small group of technology and semiconductor companies to drive earnings growth, such a shift could have broader consequences.

The AI Trade Does Not Need to Burst to Become a Problem

Snider's argument also moves away from the binary question of whether AI is a bubble.

Goldman is not forecasting an immediate collapse in AI investment or a sudden reversal in technology stocks. In fact, Snider previously argued that investors should increase exposure to popular AI infrastructure stocks, citing the strength of the data-center investment cycle.

The latest assessment is instead about the changing economics of that cycle.

The first phase of the AI boom rewarded companies capable of supplying scarce computing capacity. Demand vastly exceeded available supply, allowing chipmakers and other infrastructure providers to increase both revenue and margins.

As the industry expands capacity, that scarcity premium can begin to diminish. This means AI spending can remain enormous while becoming less powerful as a driver of incremental earnings. A company spending billions more on AI infrastructure does not necessarily translate into an equivalent increase in profits for its suppliers or customers.

Goldman's concern is thus relevant to investors who have extrapolated the earnings growth of the past several years far into the future.

The market has already priced a substantial amount of future AI growth into technology valuations. If earnings continue rising but at a slower rate, the justification for those valuations becomes more dependent on how investors assess future growth, margins, and cash generation.

'Other Income' Adds Another Earnings Headwind

Goldman sees another source of earnings growth fading: gains from companies' private investments. Some major companies have generated income from increases in the value of private investments. Those gains can appear in reported earnings even though they do not necessarily represent cash generated by the underlying business.

Goldman expects that contribution to become significantly smaller in 2027.

"We expect a much smaller contribution in 2027. The complete removal of this 'other income' next year would create a drag of 8 pp on S&P 500 earnings growth in 2027 relative to 2026, all else equal," Snider said.

That creates a second potential earnings headwind alongside semiconductor margins.

The combination is considered vital because the S&P 500's earnings growth has increasingly benefited from several powerful forces operating simultaneously: AI infrastructure spending, exceptional profitability among technology companies and investment-related gains. If those contributions normalize at the same time, the headline earnings picture could change even without a recession or a collapse in corporate technology spending.

For investors, the question therefore becomes less about whether the AI boom is ending and more about how much of its economic benefit has already been captured by the companies and suppliers at the center of the cycle.

Goldman's outlook suggests the next phase of the AI trade may be considerably more demanding. Continued spending can support revenues across the technology ecosystem, but sustaining rapid earnings growth will require companies to convert that spending into durable profits rather than simply larger infrastructure footprints.