Watch out for hidden AI bets and rising concentration risk, Morningstar warns

Artificial intelligence may be the dominant market theme, but it's as much a risk-management problem as it is a growth opportunity, according to an analysis from Morningstar.

In its 2026 Global Outlook, analysts from Morningstar said the AI boom is less about consumer-facing tools and more about a massive, capital-intensive buildout in data center infrastructure led by a handful of US tech giants.

“The artificial intelligence age is upon us, and it isn’t just about ChatGPT – it’s about a global construction boom,” the report's authors wrote.

Hyperscalers such as Microsoft, Amazon, Alphabet, Meta, and Oracle have committed astronomical sums to AI capacity, with combined capital expenditures projected to surpass four times the spending of the entire US energy sector in 2026. 

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Citing data from FactSet, Morningstar said the five tech giants' projected capex for 2026 is roughly $450 billion, significantly above the estimated $375 billion in capital spending this year.

“Collectively, hyperscalers are spending hundreds of billions of dollars each year on capital expenditures, much of it dedicated to data center expansion,” Morningstar noted.

That scale brings new forms of execution and macro risk that RIAs and broker-dealer advisors may have to factor into portfolio construction. Morningstar flags the strain on power grids and local resources as a key vulnerability, pointing out that GPUs are extremely energy intensive and that data centers also rely heavily on water for cooling. Between community pushback and infrastructure bottlenecks, those buildouts could see delayed implementation or increase costs over time.

Monetization is another open question. Despite AI tools now being firmly embedded in consumers’ lives, paid usage remains limited and many corporate projects are still experimental. Morningstar highlighted that just 5% users currently pay for ChatGPT, even as hyperscalers plan multi-year spending programs. If revenue ramps more slowly than capex, return-on-investment targets may prove overly optimistic.

"During the dot-com era, 'clicks' and 'eyeballs' drove valuations that weren’t backed by profits," Morningstar said. "People may like chatbots when they’re free, but how much will they actually pay per month to use them?"

The report also stressed how most US investors are already heavily exposed to the AI trade, whether they know it or not. AI-linked names dominate major benchmarks, and Morningstar’s own thematic index work shows that companies tied to next-generation AI now account for a large and rising share of broad US equity indexes.

“Over the past 10 years, the stock market has grown increasingly concentrated in AI-related names,” the authors noted, with a small cluster of mega-caps driving a disproportionate share of gains.

Given elevated valuations in technology and communication services, Morningstar encouraged investors to lean into balance rather than chase the theme. For those concerned about concentration risk, the analysts suggested tilting toward US value and small-cap stocks – which they saw as trading below fair value and carrying far less direct AI exposure – and to look at selected foreign markets where AI’s influence on index-level performance is more muted.