S&P 500 Earnings Slowdown Expected as AI Capex Fades

Goldman Sachs forecasts a deceleration in S&P 500 earnings growth rather than a collapse, projecting EPS to rise 11% to $415 in 2027 and another 11% to $460 in 2028. This outlook, sourced from GN markets/earnings (en-US), indicates that the index is running ahead of its long-run trend, with Q2 EPS up 51% year-over-year. The bank attributes this surge to extraordinary AI spending, semiconductor margins, and private investment gains, though it warns that this pace is unsustainable without a shift in the underlying economic engine.

The primary concern is the fading contribution of AI capital expenditure to corporate profits. Rising depreciation costs will erode the earnings tailwind from AI infrastructure, reducing its impact from 11 percentage points in 2026 to a marginal drag by 2028. This transition marks a critical handoff from building AI infrastructure to utilizing it for productivity gains, a shift that determines whether the current earnings boom can be sustained in the medium term.

Semiconductor Margins Present Sharpest Risk

Semiconductor margins represent the most significant fault line for S&P 500 earnings. A return to historical gross margin levels could remove approximately 10% from total index earnings. This volatility highlights the dependence of the broader market on specific high-margin sectors, making the overall earnings picture fragile if normalization occurs in the tech hardware supply chain.

Valuation Relies On Earnings Growth

Goldman Sachs maintains a 12-month target of 8,700 for the S&P 500, but this projection is driven entirely by earnings growth rather than multiple expansion. The bank’s base case assumes solid economic growth and easing energy pressures, but it does not rely on investors paying a premium for risk. This approach underscores that the market’s next leg up depends on the quality of the AI productivity handoff rather than speculative re-rating.

Productivity Transition Defines Future Returns

The distinction between over-earnings and an earnings bubble hinges on the transition from capital expenditure to productivity. Traders are no longer debating the existence of AI benefits, but rather whether the profits generated during the infrastructure build-out can survive once the construction phase concludes. The sustainability of S&P 500 returns now rests on companies successfully converting AI investments into tangible operational efficiencies.