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Gartner forecasts that power availability will operationally constrain 40% of existing AI data centers by 2027. That is a prediction, not a report that 40% are already short of electricity. The issue is whether power can be delivered to a site at the capacity and pace operators need—not simply whether enough electricity is generated in aggregate.
What Gartner’s 40% forecast means
In a November 12, 2024 announcement, Gartner said 40% of existing AI data centers would be operationally constrained by power availability by 2027. The announcement does not provide a detailed methodology or geographic breakdown, so the estimate should be treated as Gartner’s forecast rather than a verified, uniform outlook for every country or operator. Gartner’s 2024 announcement
A facility can face a power constraint even when electricity is being generated elsewhere. Generation must be supplemented by the transmission and distribution infrastructure needed to deliver power to the site, and utility expansion takes time. Gartner says the rapid growth of new hyperscale facilities for generative AI is increasing demand faster than utilities can expand capacity.
How much power Gartner expects AI servers to need
Gartner estimated that data centers would need 500 terawatt-hours (TWh) per year in 2027 to run incremental AI-optimized servers. It described that requirement as 2.6 times the 2023 level. This figure refers to incremental power for those AI-optimized servers; it is not an estimate of total electricity use by all data centers. The same announcement said data center forecasts over the following two years reached as high as 160% growth. These are Gartner estimates and forecasts, not measured outcomes, and the announcement does not detail how the figures were calculated. Gartner’s 2024 announcement
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Why electricity delivery can become a bottleneck
Gartner’s concern is that new data-center demand can arrive sooner than the infrastructure required to serve it. New generation, transmission lines and distribution capacity may take years to come online, while data-center operators need power for facilities they are planning or expanding now. In that situation, available power can influence where projects are built, how quickly they open and whether they can operate at planned capacity. Gartner warned that power availability could govern near-term data-center construction and generative-AI growth.
The effects will depend on local conditions. Gartner’s announcement does not break down its forecast by country, grid or operator, and it does not establish that every data center will face the same degree of constraint.
Potential cost and emissions effects
Gartner warns that competition for power could raise data-center operating costs and pass costs through to AI and generative-AI service providers. That is a risk Gartner identifies, not a guarantee that costs will rise by the same amount for every operator or customer. Its announcement gives no common price increase to apply across markets.
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Gartner also says fast-rising demand could make emissions goals harder to meet if suppliers rely on short-term power sources, including keeping some fossil-fuel plants online longer than planned. It notes that wind and solar need an alternative supply when they are not generating if data centers require continuous power. This is Gartner’s analysis of the challenge, not a full assessment of storage, grid balancing or clean-energy contracting.
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What data-center operators can assess now
Gartner recommends evaluating exposure to power shortages and planning for electricity costs, rather than assuming that planned utility capacity will arrive on schedule. Its recommendations include:
- Assess which products and services depend on facilities or regions exposed to power constraints.
- Anticipate the possibility of higher power costs and consider long-term data-center service contracts that account for power.
- Revisit emissions goals against expected power requirements and the reliability of the available supply.
- Reduce the computation required for generative-AI applications where practical; Gartner names smaller language models and edge computing as options to evaluate.
These are planning measures, not a promise that any single action will remove a site’s power constraint. The appropriate response depends on the application, location, grid access, cost and reliability requirements.
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Could small modular reactors help?
Gartner presents small modular reactors (SMRs) as a possible longer-term source of dedicated on-site power, not a near-term fix. In an April 15, 2025 Q&A, Gartner analyst Bob Johnson said the company forecasts that the first SMR-powered data centers will be operational by 2030. The same Q&A says general availability may be 8–10 years away, early models will be expensive, radioactive waste must be managed, and regulatory and development challenges remain. Gartner also describes the concept as unproven. Gartner’s 2025 SMR Q&A
Those dates are Gartner forecasts, not confirmation that an SMR-powered data center is operating or that reactors will become available on a particular schedule. Operators weighing the option would need to consider cost, dependable delivery, emissions, site and grid conditions, and regulatory and technology readiness.
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