The rapid expansion of artificial intelligence is creating an unexpected bottleneck across the United States, shifting investor attention from semiconductor shortages to electricity supply. According to Morgan Stanley, the growing demand for AI data centers is expected to create a substantial power deficit through 2028, positioning companies that generate or supply electricity as some of the biggest beneficiaries of the next wave of AI infrastructure spending.

Among those companies, GE Vernova appears particularly well positioned due to its leadership in large-scale natural gas turbines, which Morgan Stanley identifies as the single largest solution for addressing the projected power shortage.

AI Infrastructure Faces a Growing Power Gap

Morgan Stanley estimates that U.S. data centers will require approximately 68 gigawatts (GW) of additional electricity between 2026 and 2028. Current projects under construction are expected to provide only about 15 GW of new generation capacity, while another 15 GW is expected to come from existing or contracted grid resources.

That leaves an estimated 38 GW gap before alternative energy solutions are considered.

Even after incorporating multiple supplemental power sources into its analysis, Morgan Stanley projects the U.S. could still experience an electricity deficit ranging from 1 GW to 11 GW through 2028.

The report suggests that limited electricity availability could delay AI data center construction, increase development costs, tighten regional electricity markets, and elevate wholesale power prices.

Natural Gas Turbines Offer the Largest Near-Term Solution

Morgan Stanley identified several technologies capable of reducing the projected electricity shortage.

Natural gas turbines represent the largest potential contributor, with an estimated capacity of 15 GW to 20 GW.

Fuel cells could provide an additional 5 GW to 8 GW, while co-located nuclear facilities may contribute another 3 GW to 5 GW. Existing Bitcoin mining facilities with established grid connections could potentially be converted into AI data centers, supplying between 10 GW and 19 GW of capacity.

Despite these options, Morgan Stanley concludes that electricity demand is likely to outpace available supply for several years.

GE Vernova Positioned to Benefit

GE Vernova stands out because it is the market leader in large-frame natural gas turbines, equipment widely viewed as one of the fastest and most practical methods for adding new generating capacity.

The company already maintains a multiyear order backlog, supported in part by growing demand from AI-related infrastructure projects.

As hyperscale technology companies continue building increasingly power-intensive data centers, demand for gas turbine equipment is expected to remain strong, particularly as utilities seek reliable generation sources that can be deployed more quickly than many renewable or nuclear alternatives.

Other Energy Companies Could Also Benefit

Morgan Stanley also identified several other companies positioned to benefit from the AI-driven electricity shortage.

Bloom Energy could see increased demand for its fuel cell technology, which can often be deployed faster than waiting for traditional grid interconnections.

Constellation Energy, Vistra, and Talen Energy may benefit from their existing nuclear generation assets, which could support co-located AI data center developments.

Meanwhile, Bitcoin mining companies including Core Scientific, IREN, and Cipher Mining possess existing grid-connected infrastructure that could potentially be repurposed into AI computing campuses, reducing the lengthy wait times typically associated with securing new electricity connections.

Power Supply Becoming the Next Competitive Advantage

The report suggests that access to electricity is rapidly becoming one of the most valuable assets in the AI economy.

While semiconductor manufacturers remain essential to AI development, computing hardware cannot generate economic value without reliable power. Companies that already own generating capacity or possess infrastructure capable of supplying electricity may therefore become increasingly important participants in the expanding AI ecosystem.

As the industry moves beyond acquiring advanced chips and toward securing reliable energy supplies, investors may increasingly evaluate power infrastructure alongside traditional AI technology companies.

Closing Insights

Morgan Stanley’s analysis highlights a fundamental shift in the AI investment landscape, where electricity availability is becoming as critical as semiconductor supply. With a projected power deficit extending through 2028, companies capable of delivering reliable generation capacity are positioned to play an increasingly important role in supporting AI infrastructure. Among those firms, GE Vernova’s leadership in natural gas turbines and its existing order backlog place it in a strong position to benefit as hyperscale data center developers race to secure the power needed for the next generation of artificial intelligence.