Goldman Sachs reports S&P 500 Q2 earnings up 31%. AI infrastructure firms drove half of growth. Only 2% of companies quantified AI earnings impact. Enterprise spending rising fast.
The earnings boost from artificial intelligence remains concentrated in a narrow slice of the S&P 500, even as enterprise spending on AI climbs sharply, according to a Goldman Sachs report.
S&P 500 earnings grew 31% year over year in the second quarter of 2026. AI infrastructure companies and hyperscalers – the firms building and selling the computing backbone for AI – posted 54% earnings growth and accounted for roughly half of the index's total increase. Exclude energy, and the rest of the market still grew 14%.
The direct effect on most corporate bottom lines is small. Only 11% of S&P 500 companies quantified AI productivity gains for a specific use case, Goldman Sachs found. Just 2% put a number on the earnings contribution. Companies that did disclose such gains did not show a statistically meaningful advantage in earnings growth over peers.
Enterprise AI spending is climbing fast. The median company spent $12 per employee per month on AI in July, up from $5 at the start of the year. The top decile of spenders burned $650 per employee, compared with $240 earlier. Still, AI inference costs amount to less than 0.5% of S&P 500 revenue. About two-thirds of companies are funding the outlay by reallocating existing budgets, including software and labor lines.
Goldman Sachs said the productivity payoff should become clearer as companies move from tests to broader deployment. For now, the broker said, investors continue to favor AI infrastructure firms, where the earnings link is more direct. The longer-term winners from AI-driven efficiency remain uncertain.
The report implies that the AI trade is bifurcated. Companies selling the picks and shovels – chipmakers, cloud providers, data-center operators – are already booking the returns. For the rest of corporate America, AI is still a cost line, not a revenue driver. That gap may narrow as deployment scales, the report said, but the timing is unclear.
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