Goldman Sachs Says AI Spending Not Boosting Corporate Earnings

A jump in corporate artificial intelligence spending has not translated into a corresponding boost in earnings.

That’s according to a report Sunday (Aug. 16) by Seeking Alpha, citing an analysis from Goldman Sachs which found that just 2% of S&P 500 companies quantified the effects of AI in second-quarter earnings reports.

Of those, 11% cited measurable productivity gains in areas such as software coding or customer support, but did not report significantly stronger growth than the rest of the market, the analysis said. Median earnings from those companies rose 17%, compared to 14% among companies that did not quantify productivity gains from AI.

The Seeking Alpha report said these findings help show why the market keeps rewarding companies involved in the AI infrastructure boom such as semiconductor firms, cloud-computing providers while showing skepticism toward companies pledging productivity gains still to come.

Spending on infrastructure has driven measurable revenue and profit growth, while the potential benefits from corporate AI adoption remains hard to gauge and may take several quarters to materialize. Earnings among hyperscalers and other firms benefiting from AI capital investments surged by 54%, representing about half of the index’s earnings growth, the report added.

The Seeking Alpha report also noted evidence that AI adoption may become more visible in corporate results in quarters ahead.

Median monthly AI spending per worker climbed to $12 in July, compared to $5 at the beginning of the year, according to the Ramp AI Index cited by Goldman Sachs. And spending among the top 10% of companies jumped to $650 per employee, up from $240 earlier this year.

Meanwhile, research by PYMNTS Intelligence shows that a growing share of chief financial officers expect to see a return on AI investments within one to two years.

As covered here last week, a survey last year of CFOs at large U.S. companies found that no finance chief expected generative AI to produce very positive returns within one to two years.

However, that number had jumped to 39.1% by the end of 2025, with the share  expecting that level of return in three to five years from 65.9% to 34.8%.

“That movement suggests targeted projects are starting to show a clearer path to value,” PYMNTS wrote.

The research also found that full integration will take time. CFOs projected that embedding AI throughout their company would take 6.28 years on average, nearly double the 3.19 years they forecast in July of last year.

“They appear to view the rollout like renovating a building one floor at a time: individual spaces can improve quickly while the complete project takes longer,” the report added.

“That distinction helps explain why near-term confidence and longer implementation schedules can rise together.”

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