Few forces have shaped this year’s results more than artificial intelligence, and here too, reality has run ahead of expectations. The largest US technology companies, known as hyperscalers, spent about $150 billion on capital investment in 2023. This year, they are on track to spend about $800 billion, more than five times as much in just three years. Each year, actual spending has exceeded analysts’ forecasts at the start of the year.

That spending is a direct source of profits for the companies building AI infrastructure, including chipmakers, hardware makers, industrial firms, and utilities. Excluding one-time “other income” gains, those companies account for roughly half of S&P 500 earnings growth this year.1 Much of every dollar a hyperscaler spends on a data center shows up as revenue for another company in the index.

The natural question is, what happens if the spending slows or stops growing? Analysts do expect hyperscaler spending growth to decelerate in the coming years, but we see little chance of spending plateauing in the foreseeable future. Hyperscalers are expected to spend more than $1 trillion next year. To stall overall S&P 500 earnings growth next year, that spending would have to fall by nearly a third from this year’s level. That would be a sharp reversal, and nothing in companies’ current plans points to one. Even then, profits for the companies supplying the AI buildout would remain roughly 25% above 2025 levels.2 The managers and companies we speak with consistently tell us that demand for AI capacity is meaningfully outpacing supply.

There are also growing signs that the spending is paying off. Cloud revenue growth at Amazon, Alphabet, Microsoft, and Oracle is expected to accelerate from +48% in the second quarter to +55% in the third, supported by large backlogs of contracted business. Nearly 30% of S&P 500 companies mentioned AI having a quantifiable impact on their latest earnings calls, up from less than 5% in early 2023.3 In our view, there is still significant room for AI adoption to expand.

Investors broadly expect AI spending to keep growing, and we share that view. Where they are more cautious is in how long today’s exceptional growth and profitability can last, and NVIDIA is a striking example. Last quarter, NVIDIA grew revenue +105% with EBITDA margins of nearly 70% and raised its outlook, yet the stock trades at about 18x forward earnings, down from 32x a year ago. That discount reflects uncertainty about how durable those results will be. Who ultimately captures the economics of AI remains an open question. Given how wide the range of outcomes still is, we think the prudent approach is to maintain broad exposure across the AI ecosystem and beyond, rather than concentrating on the few companies leading today.


Endnotes

1,2 Goldman Sachs Global Investment Research, “US Equity Views: Over-earning, but not an earnings bubble,” September 17, 2026.

3,4 Sourced from a16z State of the Markets September 2026. AlphaWise and Morgan Stanley Research, July 27, 2026. “AI adopters” are companies identified by Morgan Stanley Research analysts. Companies reporting multiple quantifiable benefits from artificial intelligence are counted only once. The analysis is based on company disclosures and may not capture benefits that have not been publicly quantified.

5 FactSet and Goldman Sachs Global Investment Research. Hyperscaler capital-spending growth represents consensus estimates for Amazon, Alphabet, Meta, Microsoft, and Oracle.

6 Goldman Sachs Global Investment Research. Cloud revenue growth represents the aggregate year-over-year growth of Amazon, Alphabet, Microsoft, and Oracle cloud businesses. Q3 and Q4 2026 figures are Goldman Sachs estimates.