Wall Street bulls are pointing to strong corporate earnings growth as a fundamental pillar supporting equity markets hovering near record highs this season.
Strategists at Goldman Sachs, led by Ben Snider, report that earnings per share growth for the second quarter is running at 31% year-over-year, even excluding “other income” tied to private investment stakes.
The Goldman team estimates that artificial-intelligence infrastructure stocks have accounted for roughly half of that overall EPS growth, underscoring how concentrated the AI earnings boom remains.
Broader market earnings have also been strong, with the median S&P 500 company growing EPS by 14%, suggesting the rally has more fundamental support than many critics acknowledge.
Despite those encouraging numbers, Snider and his colleagues caution that the “impact of AI adoption on corporate earnings still appears narrow” across the wider corporate landscape.
So far this earnings season, only 11% of S&P 500 companies have quantified the impact of AI productivity on a specific use case, such as coding or customer support, according to Goldman.
Just 2% of firms have quantified AI productivity’s impact on earnings directly, a figure roughly unchanged from the first quarter of 2026, highlighting how early the adoption curve truly is.
That uncertainty has shaped investor behavior, with markets rewarding AI infrastructure plays that offer clear near-term earnings while largely avoiding broader productivity beneficiary bets.
Enterprise AI spending is nonetheless accelerating sharply, with the Ramp AI Index showing monthly AI spend per employee at the median company rising from $5 in January to $12 in July.
Goldman Sachs built its stock screen by targeting select Russell 1000 firms with high wage bills exposed to AI automation, high labor costs, and recent earnings call mentions of AI in the context of productivity or efficiency.
Companies already included in Goldman’s AI infrastructure or AI disruption risk baskets were excluded, keeping the focus squarely on productivity beneficiaries outside the core tech buildout trade.
The screen’s constituents have gained 17% since December 2023, trailing the equal-weight S&P 500’s 23% gain over the same stretch, leaving room for meaningful catch-up if AI productivity gains materialize.
Goldman’s strategists noted that “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,” but expect that picture to sharpen.
The top 20 stocks ranked by labor cost sensitivity and AI automation exposure include CoStar, Dollar Tree (DLTR), and eBay (EBAY) among the leading names on the list.
Insurance and financial services firms feature prominently, with Arthur J. Gallagher (AJG), Brown and Brown (BRO), Aon (AON), Marsh and McLennan (MMC), and Willis Towers Watson (WTW) all making the screen.
Industrial and defense names Boeing (BA) and RTX (RTX) appear alongside infrastructure and real estate plays Iron Mountain (IRM) and CBRE (CBRE) in the Goldman ranking.
Technology-adjacent companies including Axon Enterprises (AXON), Trade Desk (TTD), and Expedia (EXPE) round out the list alongside consumer staples name Kimberly-Clark (KMB).
Energy and utility firms CMS Energy (CMS) and Edison International (EIX) also make the cut, reflecting how broadly AI-driven labor cost savings could touch regulated industries with large workforces.
Jacobs Solutions (J) and Airbnb (ABNB) complete the top 20, spanning engineering services and travel platform sectors where automation of labor-intensive workflows could deliver meaningful margin improvement.
Goldman’s broader message is that while AI’s productivity payoff remains difficult to quantify today, the companies best positioned to capture it are those already managing high labor costs and actively integrating AI tools into their core operations.
