The AI Boom Just Drove S&P 500 Profits 51% Higher, but Its Biggest Tailwind Is Fading
S&P 500 earnings just posted their strongest growth in years, and Goldman Sachs says AI infrastructure deserves most of the credit. But the same spending wave that inflated profits is quietly engineering a reversal that most investors have not yet…
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The S&P 500 just produced the kind of earnings growth that can make a bull market look self-sustaining. Earnings per share jumped 51% year over year in Q2, while trailing 12-month EPS rose 26%, compared with an average annual gain of roughly 7% over the past 30 years. But there’s a catch: Goldman Sachs Research says much of that acceleration is tied to AI spending, soaring semiconductor margins, and investment gains that won’t keep contributing at today’s rate. The next leg of the market depends on whether AI can turn an investment boom into a productivity boom.
The $800 Billion AI Earnings Machine
Goldman Sachs chief U.S. equity strategist Ben Snider estimates that almost half of 2026 S&P 500 earnings growth can be attributed to AI-related investment.
Amazon (NASDAQ:AMZN | AMZN Price Prediction), Meta Platforms (NASDAQ:META), Alphabet (NASDAQ:GOOG), Microsoft (NASDAQ:MSFT), and other hyperscalers are expected to spend about $800 billion on capital expenditures in 2026, up 94% from 2025.
That money becomes somebody else’s revenue. Chipmakers sell processors, hardware companies build data-center equipment, industrial companies provide power infrastructure, and utilities supply the electricity needed to run it all.
Goldman expects hyperscaler capex to climb to $1.2 trillion in 2027 and $1.4 trillion in 2028. That sounds bullish until you look at the growth rate — and the bill arriving behind it.
More data centers mean more depreciation. Goldman estimates depreciation will subtract roughly 5 percentage points from S&P 500 earnings growth in 2027, nearly half of the approximately 11-point boost from continued AI capex. By 2028, depreciation could completely offset the earnings contribution from additional AI investment.
Ultimately, the spending that created today’s earnings boom eventually starts working against it.
The Other Earnings Boosters Are Fading, Too
AI infrastructure isn’t the only temporary factor inflating profits. Memory producers are generating gross margins near 80%, more than twice historical levels, because AI demand has collided with constrained supply. Goldman expects tight supply through 2027, but it also expects the pace of margin expansion to slow. A return toward historical profitability could reduce S&P 500 earnings by roughly 10%.
Then there are unrealized gains on private AI companies. Large technology companies booked roughly $150 billion of unrealized investment gains in Q2 — equivalent to about 12% of S&P 500 EPS. Goldman expects more gains in the second half of 2026, but much less in 2027. Removing that contribution entirely would create an estimated 8-percentage-point drag on 2027 earnings growth versus 2026.
While the 51% figure is real, it just isn’t sustainable.
Stocks Can Still Climb — If AI Delivers the Next Phase
That difference is key to understanding the next leg of growth, because Goldman isn’t calling for an earnings collapse.
The firm forecasts S&P 500 EPS of $415 in 2027 and $460 in 2028, or about 11% annual growth. It also maintains a 12-month S&P 500 target of 8,700, versus roughly 7,743 at Friday’s market close, implying about a 14% gain.
To see how Goldman gets there, it is important to recognize it is not through a bigger valuation multiple.
Rather, the S&P 500’s forward P/E has fallen from 23 times earnings a year ago to 19 times today, exactly in line with its 10-year average. Goldman therefore sees no evidence of a traditional valuation bubble in the near-term multiple.
That doesn’t mean stocks are cheap. The cyclically adjusted P/E remains near one of its highest readings on record — below the 1999–2000 peak but above 2021 levels.
Key Takeaway
The AI boom isn’t quite ending, but the easy part is over. Investors have already watched $800 billion of annual AI infrastructure spending flow into corporate earnings. The harder question is what happens when that spending stops accelerating, and depreciation starts eating into the benefits.
Goldman’s 8,700 S&P target indicates stocks can keep rising even as AI’s initial earnings boost fades. But it also requires the next phase to work: AI must generate measurable productivity gains throughout the economy, rather than simply producing more revenue for the companies building the infrastructure.
For investors, that’s the number to watch now. Not how much AI companies spend — Goldman estimates hyperscaling spending could reach $7.6 trillion between 2026 and 2031 — but rather how much profit the economy ultimately gets back.
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After two decades of patrolling the dark corners of suburbia as a police officer, Rich Duprey hung up his badge and gun to begin writing full time about stocks and investing. For the past 20 years, he’s been cruising the markets looking for companies to lock up as long-term holdings in a portfolio while writing extensively on the broad sectors of consumer goods, technology, and industrials. Because his experience isn’t from the typical financial analyst track, Rich is able to break down complex topics into understandable and useful action points for the average investor. His writings have appeared on The Motley Fool, InvestorPlace, Yahoo! Finance, Money Morning, and, of course, 24/7 Wall St. He has been featured in both U.S. and international publications, including MarketWatch, Financial Times, Forbes, Fast Company, and USA Today.
