Why AI Companies May Invest More than $500 Billion in 2026

Which stocks are likely to benefit from AI?

Many investors believe that AI adoption will eventually boost economic productivity growth and benefit an expanding universe of companies. But the practical focus of most investors has primarily been on the near-term earnings beneficiaries of the current boom in AI investment spending, according to the report.

In turn, equity gains have been concentrated in AI infrastructure companies, according to Goldman Sachs Research. These include semiconductors, hyperscalers and other data center operators, technology hardware providers, and power companies. The average stock in Goldman Sachs Research’s basket of infrastructure companies returned 44% year-to-date, compared with a 9% increase in the consensus two-year forward earnings-per-share estimate for the group. “The timing of an eventual slowdown in capex growth poses a risk to these companies’ valuations,” Hammond writes.

Our researchers say attention is starting to shift to companies in other phases of the AI trade, such as companies with the potential for AI-enabled revenues. Some of those firms—primarily members of the software and services industry group—have struggled in recent months because they have yet to realize AI-enabled revenue growth. But a group of “AI Platform” stocks, which include the providers of database and development tools, have proved an exception. Their stocks have recently outperformed, and our analysts expect them to continue to benefit as corporate AI adoption increases.

The performance of stocks in another phase—AI Productivity Beneficiaries—has similarly underwhelmed as investors have struggled with the uncertainty surrounding the timing and magnitude of future earnings benefits.

Our analysts’ framework for companies that could benefit from an AI productivity uplift focuses on labor costs as a share of sales and exposure to AI automation as two key inputs. The group of potential AI Productivity Beneficiaries stocks has lagged the recent trajectory of their earnings (and their stock gains have lagged behind the broader S&P 500 index), suggesting an “attractive risk-reward for investors seeking to expand their exposure to AI beyond the infrastructure layer,” they write.

How much are hyperscaler tech companies expected to invest in AI?

If recent history holds, analyst estimates for technology capex may be revised higher still. The hyperscalers spent $106 billion in capex in the third quarter this year (including AI and non-AI expenditures), representing a year-over-year growth rate of 75%. Analysts expect this growth rate will slow sharply to 49% in the fourth quarter and to 25% by the end of 2026.

But Goldman Sachs Research notes that consensus capex estimates have proven to be too low for two years running. At the start of both 2024 and 2025, consensus estimates implied capex growth of roughly 20% for the year. In reality, it exceeded 50% in both years.

While capex spending at the large public hyperscalers has surged in the last few years, it remains far below levels indicated by previous technology investment cycles. AI capex has recently equated to 0.8% of GDP, compared with peaks levels reaching 1.5% of GDP or greater during other technology booms of the past 150 years. AI hyperscaler capex would need to reach $700 billion in 2026 to be in line with the peak of spending during the late 1990s telecom investment cycle.

For the hyperscaler companies, supply bottlenecks or investor appetite are more likely to constrain capex than cash flows or balance sheet capacity.

In fact, the magnitude of spending in historical technology investment cycles suggests as much as $200 billion upside to current hyperscaler 2026 capex estimates, Hammond and the team write. “The strong balance sheets of the largest hyperscalers—and their recent willingness to employ those balance sheets—support the outlook for continued capex spending growth.”