AI data centers use so much electricity because they run large numbers of power-hungry accelerated servers to train and operate AI models, then draw still more power for cooling and other facility systems. The global share is modest, but demand is rising quickly and facilities are clustered in places where grid capacity can be constrained.
What uses the electricity in an AI data center?
The main AI-specific load is computation. Training and serving models rely on fleets of high-performance accelerated servers, which use more power when deployed in dense clusters. The servers are only part of a facility’s electricity bill: conventional servers, storage and networking equipment, cooling, and other infrastructure also consume power.
In its 2025 base-case analysis, the International Energy Agency (IEA) projects that accelerated servers will account for almost half of the net increase in data-center electricity consumption through 2030. Conventional servers contribute around 20% of that projected increase, other IT equipment around 10%, and cooling plus other infrastructure around 20%. These are projections of the sources of growth across data centers, not measured shares of electricity use at every individual site. IEA, “Energy demand from AI” (2025)
How large is data-center electricity demand?
Worldwide data centers used 415 terawatt-hours (TWh) of electricity in 2024, or about 1.5% of global electricity consumption, according to the IEA’s 2025 report. That report’s base case projects around 945 TWh in 2030, a little under 3% of global electricity consumption in that scenario. The 945 TWh figure is a forecast, not a measured result. IEA, “Executive summary – Energy and AI” (2025)
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The IEA’s later update reports that data-center electricity demand grew 17% in 2025, while overall global electricity demand grew 3%; AI-focused centers grew faster than the data-center average. The 2026 update says data-center electricity use is set to double by 2030 and AI-center power use to triple. These later projections reflect an updated assessment and should not be combined with the 2025 report’s 945 TWh base-case forecast as though they were one forecast. IEA update (2026)
Why can efficiency improve while total use rises?
Electricity consumption for an individual AI task is declining rapidly, the IEA says. But lower energy use per task does not guarantee lower total demand: more users, more frequent use, and energy-intensive applications such as AI agents can increase the number and complexity of tasks. If that growth outpaces efficiency gains, overall electricity use rises even as each task becomes less energy-intensive. IEA update (2026)
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Why does a relatively small global share matter to local grids?
A global percentage can obscure where the electricity is consumed. In 2024, the United States accounted for 45% of global data-center electricity consumption, China 25%, and Europe 15%, according to the IEA. Nearly half of U.S. data-center capacity is concentrated in five regional clusters. Large new loads in a small number of areas can therefore matter to local grids even when data centers account for a limited share of worldwide electricity use. IEA, “Executive summary – Energy and AI” (2025)
Grid infrastructure can also take longer to plan and build than a data center. The IEA says a data center can become operational within two to three years, while energy infrastructure has longer lead times. Its 2025 analysis identifies long grid-connection queues and estimates that around 20% of planned data-center projects could risk delay unless grid risks are addressed. That is a risk across planned projects, not a prediction that any particular facility will be delayed. IEA, “Energy demand from AI” (2025)
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How much power can a facility require?
Power capacity, measured in megawatts (MW), describes how much power a facility can draw at a given moment; it is not the same as the electricity it consumes over a year, measured in TWh. The IEA describes traditional data centers as using 10–25 MW, while hyperscale AI centers can exceed 100 MW. Its household-equivalence comparisons use assumed capacities of 25 MW for a conventional facility, 100 MW for a hyperscale facility, and around 2,000 MW for the largest facility under construction. These are illustrative capacity comparisons, not universal annual-use figures for data centers. IEA, “Artificial Intelligence – Topics”
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Where does the electricity come from?
The IEA’s 2025 outlook says renewables and natural gas lead in meeting projected data-center demand, with nuclear and other sources also contributing. There is no single supply mix for all data centers; it varies by location and project. IEA, “Executive summary – Energy and AI” (2025)
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The IEA’s 2026 update reports that some developers are pursuing onsite gas generation where grid access is slow. It also warns that rapid, large swings in AI data-center demand can stretch onsite gas plants’ technical capabilities, and identifies onsite battery storage as a critical technology for the next generation of AI facilities. These are reported responses and analysis, not evidence that every center has onsite generation or batteries. IEA update (2026)
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