Just 2 percent of S&P 500 companies quantified artificial intelligence's impact on second-quarter earnings, even as enterprise AI spending more than doubled, Goldman Sachs said.
Only 11 percent of companies cited measurable AI productivity gains in areas such as software coding or customer support. Those firms posted median earnings growth of 17 percent year over year, versus 14 percent for peers that did not — a gap the brokerage said is not statistically significant.
AI infrastructure companies, including hyperscalers, saw earnings rise 54 percent year over year, accounting for roughly half of the index's 31 percent earnings growth in the quarter. Median monthly AI spending per employee climbed to $12 in July from $5 at the start of the year, while the top decile of spenders reached $650 per employee, up from $240.
The findings help explain why investors keep rewarding AI infrastructure names while discounting companies promising productivity gains still to come. Goldman expects the earnings impact of AI adoption to become more visible as companies move from experimentation to wider deployment, with roughly two-thirds funding the spending by reallocating existing software and labor budgets.
AI inference expenses currently represent less than 0.5 percent of S&P 500 revenues, keeping the immediate cost burden small, the report said. Excluding energy, S&P 500 earnings rose 14 percent year over year, showing broad strength across the market even without an AI boost.
Separate analysis from 22V Research, cited by Bloomberg, found that 25 S&P 500 firms that explicitly quantified AI's contribution during the quarter reported an average margin improvement of 180 basis points. That figure held at 150 basis points even after stripping out companies that bundled AI savings with broader productivity programs.
The margin gains are appearing across sectors, not just technology. A waste-management company reported a meaningful margin boost tied to AI-driven route optimization, according to Bloomberg, illustrating how widely the technology has penetrated enterprise workflows.
The spending trajectory suggests the payoff may arrive in coming quarters. A PYMNTS Intelligence survey found 39.1 percent of chief financial officers now expect generative AI to produce very positive returns within one to two years, up from zero a year earlier. CFOs still project full integration will take 6.28 years on average, nearly double the 3.19 years they forecast in July 2025.
For investors, the report sharpens the divide between AI infrastructure providers, where spending converts directly into revenue, and the broader corporate sector, where productivity gains remain harder to measure. Goldman's next read on the earnings impact will come as companies report third-quarter results in October.
This article is for informational purposes only and does not constitute investment advice.