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Data centers use electricity to run servers, storage, networking, cooling and other facility systems. AI is adding demand as organizations deploy more accelerated servers and run more energy-intensive workloads. The International Energy Agency’s (IEA) 2026 central projection puts data-center electricity consumption at 485 terawatt-hours (TWh) in 2025 and 950 TWh in 2030. That is a forecast, not a guarantee—and its global scale does not tell you by itself what will happen to electricity prices near any particular data center.
What uses electricity inside a data center?
A data center is more than a room full of processors. Servers process workloads; storage systems retain data; and networking equipment moves information among servers and out to users. Cooling and other facility infrastructure also need power so that equipment can operate reliably.
The IEA’s 2025 analysis estimates that servers account for around 60% of electricity demand in modern data centers on average. The share varies substantially with facility type and installed equipment, so it is not a fixed split for every site. The remaining demand includes cooling and other infrastructure as well as storage and networking.
How much electricity do data centers use?
In its 2026 central projection, the IEA estimates data-center electricity consumption at 485 TWh in 2025, rising to 950 TWh in 2030—around 3% of global electricity demand that year. It projects electricity consumption from AI-focused data centers to triple over the same period. These are estimates and projections for a changing sector, not meter readings from every facility.
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The IEA says this central demand trajectory remains close to the one in its 2025 report. It also says bottlenecks make more aggressive near-term scenarios less likely, while the longer-term outlook remains uncertain.
Why does AI increase electricity demand?
AI uses specialized, power-dense servers
Training and running AI models take place mainly in data centers. Many AI workloads use accelerated servers equipped with specialized processors. In its 2025 analysis, the IEA projected that electricity use by accelerated servers would grow faster than use by conventional servers and attributed a substantial share of net data-center demand growth to them. That is a dated model projection, not a universal measurement of every facility’s equipment mix.
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The IEA’s 2026 summary reports that AI-server power density increased elevenfold between 2020 and 2025 and is set to rise a further fourfold by 2027. Those figures describe power density, not the total electricity consumption of all data centers. The IEA also notes that training and model use can produce large, rapid power swings, making dependable supply and flexibility important.
Efficiency per task and total demand are different questions
The energy efficiency of AI tasks has improved rapidly, according to the IEA. But lower electricity use for an individual task does not necessarily lower total consumption if more people use AI or if the tasks themselves become more demanding.
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The IEA says a simple text query typically uses less electricity than running a television for the same period. That comparison should not be generalized to every AI interaction: video generation, reasoning and agentic tasks can use hundreds or thousands of times more energy per query than simple text generation. The energy used by one query is therefore a poor stand-in for the electricity used by the whole data-center sector.
Where does the electricity come from?
Data-center demand does not map to one electricity source. In the IEA’s 2025 base-case supply scenario, renewable generation grows fastest and meets nearly half of the additional electricity demand from 2024 to 2030; natural gas and coal together meet more than 40% of that increase. These are scenario results from the 2025 analysis, not a claim that every facility receives the same mix.
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The same 2025 analysis projected generation supplying data centers to rise from 460 TWh in 2024 to more than 1,000 TWh in 2030. This is a generation-to-supply projection, not the same measure or forecast vintage as the IEA’s 2026 estimate of data-center electricity consumption. The two series should not be combined as if they were directly comparable.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Can data centers affect local electricity bills?
A global share can obscure local pressure. Data centers are concentrated in particular regions and need large, reliable grid connections. The effect on electricity prices depends on local supply and demand, investment needs, a facility’s load shape and policy choices—not just the global amount of data-center consumption.
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Where a power system is already tight, new demand may require additional generation or grid upgrades. Where supply is ample, added demand may make better use of existing assets. Risks arise when data-center construction and connection requests move faster than power-system investment, or when uncertain peak loads make it difficult to plan and allocate costs fairly. That is why the same global growth forecast can have different consequences in different places; it does not establish that bills will rise everywhere.
What could change the outlook?
The IEA identifies AI adoption, grid connections, energy equipment, chip supply, project pipelines and financing as factors that could shift the pace of growth. Faster uptake of energy-intensive AI uses or the removal of deployment bottlenecks could raise longer-term demand. Efficiency gains, slower adoption or constraints on deployment could reduce it. Treat the central projection as a modeled path, not a certain outcome.
The IEA’s 2026 projection also puts data-center-associated emissions at around 350 million tonnes in 2035, or about 2% of global electricity-sector emissions. The outcome depends on both how much electricity data centers use and the sources supplying it.
What can power companies and data centers do?
The IEA discusses several ways to manage the grid impacts of growth:
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- Improve demand projections and company disclosure so planners can see likely loads and their timing.
- Manage connection queues and permitting, and allocate upgrade costs fairly.
- Consider flexible or non-firm grid connections and demand response where operational requirements allow them.
- Use batteries or on-site generation to help facilities interact with the grid, while recognizing that these measures do not replace wider grid upgrades or resolve every bottleneck.
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