Much of the second-quarter earnings season is in the bag, and equity-market bulls can argue the growth in corporate profits is acting as a fundamental support for stocks that sit around record highs.
Strategists at Goldman Sachs led by Ben Snider note that, even with “other income” related to some private investment stakes excluded, earnings-per-share growth so far for Q2 is 31% over the the same period last year.
The Goldman team estimates that artificial-intelligence infrastructure stocks have accounted for about half of that EPS growth. Still, earnings growth for the rest of the market has also been strong and accelerating, they observe, with the median S&P 500 company growing EPS by 14%.
However, in commentary published at the end of last week, Snider and colleagues also note that the “impact of AI adoption on corporate earnings still appears narrow.”
So far this earnings season, 11% of S&P 500 companies quantified the impact of AI productivity on a specific use case, such as coding or customer support, Goldman notes. And just 2% quantified the impact of AI productivity on earnings, a similar share to that of the first quarter of 2026.
“Q2 results showed a small and statistically insignificant difference in earnings growth between the companies quantifying AI productivity gains this quarter and other S&P 500 companies,” Goldman says.
However, the bank believes that a recent acceleration in enterprise AI spending suggests that the earnings impact of AI adoption should become clearer in coming quarters.
“We estimate that AI inference expenses currently equate to less than 0.5% of S&P 500 revenues, but spending appears to have accelerated sharply in recent months,” Goldman says, citing an upturn in the Ramp AI Index of monthly spend per employee.
And, as AI adoption increases, companies’ productivity should improve. “Our economists have noted that academic studies and company anecdotes show a 20-30% uplift in labor productivity in the limited areas where generative AI has been deployed, and they find that industries with higher AI adoption rates are showing a slight acceleration in productivity growth over the past year in official U.S. data,” says Goldman.
Currently, investors are more keen on AI infrastructure stocks than potential AI productivity beneficiaries, Goldman acknowledges. But this may shift, and so Goldman has run a screen for companies currently deemed most likely to benefit from AI adoption, with a particular focus on how the technology may reduce labor costs.
“To understand the labor cost sensitivity of firms, we use our estimate of each company’s labor costs as a share of revenue based on reported data. For AI exposure, our economists calculate the share of each company’s wage bill that is exposed to AI automation based on occupation-level data from Revelio,” says Goldman. Revelio Labs provides workforce analytics.
The Goldman team looks in its commentary at Russell 1000 stocks that rank in the top 50% of their sector based on the share of their wage bill that is exposed to AI automation and also rank in the top 50% of their sector based on labor costs as a share of sales.
“We further limit the screen to companies that mentioned AI in the context of productivity or efficiency during their 2Q earnings calls. We exclude companies that fall into various GS AI infrastructure or AI disruption risk baskets,” the Snider team adds.
The top 20 stocks in the screen, rated by their average rank for the labor-cost sensitivity and AI automation exposure, are the following: CoStar, Dollar Tree, eBay, Arthur J. Gallagher, Brown & Brown, Axon Enterprises, Trade Desk, CMS Energy, Jacobs Solutions, Edison International, Aon, Marsh & McLennan, Kimberley-Clark, Willis Towers Watson, Airbnb, Iron Mountain, CBRE, RTX, Boeing and Expedia.
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