Goldman Sachs: Hyperscaler AI Spending Will Continue to Support European Equities

Hyperscalers — the largest technology companies building cloud and AI infrastructure — will continue to increase capital expenditures, and this will continue to fuel profit growth in other sectors and regions, including Europe. This assessment was given by Peter Oppenheimer, chief global equity strategist at Goldman Sachs, in a comment to Bloomberg Television.

Who Are Hyperscalers

Hyperscalers are companies that manage the world's largest cloud and data center capacities — primarily Microsoft, Amazon, Google (Alphabet), and Meta. Over the past several years, these companies have consistently increased capital investments in data center construction, AI accelerator procurement, and energy infrastructure for training and operating large language models. The quarterly reports of each of them regularly serve as an indicator of the state of the entire AI industry — from semiconductor factory capacity utilization to electricity demand in regions where new data center campuses are being built.

The sharp increase in capital expenditures on AI infrastructure among hyperscalers began in 2023 amid the generative AI boom and has not reversed once since, despite periodic investor concerns about market overheating and questions about whether such investments are paying off as quickly as spending itself is growing.

Why the Effect Extends to Europe

According to Oppenheimer, growth in hyperscaler spending translates into profit growth far beyond the technology companies themselves. Part of this effect reaches Europe: local equipment manufacturers, engineering and energy companies, data center component suppliers, and cooling system providers receive orders from the global wave of AI investments. Goldman Sachs views this spillover effect as one of the factors supporting European stock indices alongside traditional growth drivers.

Among specific European beneficiaries of this wave of investments, the Dutch ASML is often mentioned — a near-monopoly supplier of lithographic equipment for advanced chip manufacturing, as well as engineering, construction, and energy companies engaged in powering and cooling new data center campuses across the continent. Their revenues and production capacity utilization depend directly on how quickly American hyperscalers continue to expand their AI infrastructure.

A separate topic increasingly discussed in connection with hyperscaler capital expenditures is energy consumption: the growth in electricity demand from AI data centers is forcing energy companies and regulators to revise network development plans for years ahead, and in some regions — to discuss extending the service life of existing generating capacity. This is why analysts include not only IT contractors and chip manufacturers, but the entire energy sector — from grid operators to turbine suppliers — among the beneficiaries of AI capital expenditures.

Are There Risks to This Bet

Analysts have been debating for several quarters whether the scale of capital expenditures on AI infrastructure is justified by the revenues these investments so far bring. Skeptics point to the risk of excess capacity and cross-financing schemes between cloud providers, chipmakers, and AI labs. Goldman Sachs' position, voiced by Oppenheimer, is optimistic: as long as hyperscaler investments continue to translate into profit growth in adjacent industries and regions, the market views this capital spending cycle as a positive factor, not a bubble.

What This Means

Goldman Sachs' assessment confirms a thesis increasingly heard in markets: capital expenditures of hyperscalers on AI have become a macroeconomic factor influencing profit growth of companies far beyond the US and the technology sector itself.