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AI data centers use electricity for two linked jobs: running computing equipment that trains and serves AI models, and operating the facility that keeps that equipment connected, powered and cool. The latest International Energy Agency (IEA) central forecast, published in its 2026 update, puts worldwide data-center consumption at about 485 terawatt-hours (TWh) in 2025 and 950 TWh in 2030—roughly 3% of global electricity demand by 2030. That is a forecast, not a measured future outcome. Growth is being driven mainly by accelerated AI servers, higher power density and expanding digital services, but chips, electricity equipment, grid connections and efficiency improvements make the path uncertain.
What electricity does inside an AI data center
A data center is an industrial building full of servers, storage, networking equipment and support systems. An AI facility has the same basic architecture as a conventional facility, but a larger proportion of its computing is performed by specialized accelerators such as graphics-processing and other AI chips. Electricity is consumed both by the digital work and by the physical systems that allow that work to run continuously.
Servers perform the computing
Servers are the largest electricity user in a modern data center, averaging about 60% of consumption in the IEA’s 2025 analysis. They contain central processors, memory, storage interfaces and, in AI systems, accelerator cards or modules. Training a model repeatedly processes enormous data sets; serving a model answers user requests. Both activities require electricity, although the amount per task depends on the model, precision, utilization and software.
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Storage systems retain training data, model weights, logs and user content. The IEA gives storage an indicative average share of about 5%. Networking equipment links servers to one another and to outside users; it can account for up to 5%. These percentages vary with the workload and design, so they should not be treated as a universal allocation for every site.
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Cooling removes heat
Almost all electricity entering a server becomes heat that must be removed. Fans, pumps, chillers, cooling towers, heat exchangers and environmental controls keep equipment within safe temperature and humidity ranges. Cooling uses about 7% of electricity in efficient hyperscale facilities but more than 30% in less-efficient enterprise data centers, according to the IEA. AI hardware can increase this burden because dense accelerator racks release more heat in the same floor area. Air cooling remains common, while liquid-cooled designs are increasingly used where rack densities exceed what room air systems can handle.
Power-conditioning and backup systems provide continuity
Uninterruptible power supplies (UPS), batteries, switchgear and backup generators protect against voltage disturbances and outages. They consume some electricity in normal operation and more during testing or an outage, but generators are rarely used compared with servers and cooling. Redundancy means a facility can keep critical workloads running while equipment is serviced or a utility fault is resolved.
| Facility function | Indicative electricity share or role | Important qualification |
|---|---|---|
| Servers | About 60% on average | Average from the IEA’s 2025 analysis; varies by equipment and utilization |
| Storage | About 5% | Indicative average, not a fixed rule |
| Networking | Up to 5% | Can be higher or lower depending on traffic and architecture |
| Cooling and environmental controls | About 7% in efficient hyperscale sites; over 30% in less-efficient enterprise sites | Facility efficiency and climate strongly affect the share |
| UPS, batteries and generators | Reliability infrastructure; generators are rarely used | Share depends on redundancy, operating conditions and testing |
Why AI raises electricity use faster than ordinary computing
Accelerated servers are expanding rapidly
The IEA’s 2025 base case projected electricity use by accelerated servers—systems used mainly for AI—to grow about 30% per year, compared with 9% for conventional servers. Accelerated servers accounted for almost half of the projected net increase in data-center consumption through 2030 in that analysis. The comparison describes the report’s modeled categories, not a guaranteed growth rate for every operator.
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AI processors are installed in dense clusters so they can exchange data at very high speed. The IEA’s 2026 update says AI-server power density rose elevenfold between 2020 and 2025 and was projected to increase another fourfold by 2027. Higher density makes each room or rack more productive, but it also concentrates electrical demand and heat. A site may therefore need heavier wiring, larger transformers, liquid cooling and new fire-safety or structural measures even when its building footprint changes little.
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Training and serving are different workloads
Training runs can keep thousands of accelerators busy for weeks or months and create a large, sustained load. Serving (inference) runs many smaller jobs, but demand can continue around the clock as applications add text, image, audio or video generation. A popular service may need spare capacity for sudden peaks, so installed power can exceed the average load. Software optimization, model compression, batching and more efficient chips can reduce electricity per answer; rising usage can still offset those savings.
How much electricity data centers use
Two IEA report editions give different baselines. They should not be blended because they use different publication years and starting estimates.
| IEA edition and measure | Data-center electricity figure | How to read it |
|---|---|---|
| 2026 update, central projection | About 485 TWh in 2025, rising to about 950 TWh in 2030 | Forecast; approximately 3% of global electricity demand in 2030 |
| 2026 update, AI-focused facilities | Consumption triples from 2025 to 2030 | Forecast for the AI-focused segment, not all data centers |
| 2025 IEA report estimate | About 415 TWh in 2024, around 1.5% of global electricity consumption | Earlier estimate with a different baseline and report vintage |
| 2025 IEA summary | About one-tenth of global electricity-demand growth to 2030; more than one-fifth of growth in advanced economies | Growth contribution, not data centers’ share of all electricity |
The 485-to-950 TWh projection means consumption would be close to doubling over five years. It does not mean every country’s use doubles, nor that all of the increase comes from AI. The IEA identifies AI as the most important growth driver while also including expanding cloud, video, communications and other digital services.
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Why demand is rising now
More AI services are moving from experiments into production
Generative assistants, search features, coding tools, recommendation systems, scientific models and automated media processing all require accelerator capacity. As organizations move from pilots to products, providers install more servers and reserve additional capacity for reliability and future growth. The IEA’s 2026 update consequently projects AI-focused consumption to triple between 2025 and 2030.
Data-center construction is faster than electricity infrastructure
A data center can become operational in roughly two to three years, according to the IEA’s 2025 analysis. New transmission lines, substations and generation projects generally require longer planning, permitting and construction periods. This timing mismatch can leave a finished building waiting for a grid connection or force developers to seek interim supplies.
Hardware and energy equipment are bottlenecks
The 2026 update identifies near-term constraints in AI chips and in equipment such as transformers and other electrical components. Those limits reduce the likelihood of the most aggressive near-term buildout scenarios. If supply improves after 2030 and energy-intensive AI uses expand, demand could accelerate again. The outcome depends on shipment volumes, utilization, software efficiency and the ability to connect new sites.
Where the impact is concentrated
Three markets dominate projected growth
The United States, China and Europe are the largest data-center markets in the IEA’s 2025 outlook. Together, the United States and China account for nearly 80% of projected global growth to 2030 in that analysis. For 2024 electricity use, the IEA attributed about 45% to the United States, 25% to China and 15% to Europe.
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These percentages describe regional totals, not a uniform distribution across each continent. Facilities cluster near fiber routes, customers, available land and power infrastructure. A local substation can therefore face a major new load even while data centers remain a modest fraction of worldwide electricity.
Global share and local grid stress are different questions
The IEA’s 2025 executive summary estimated that around 20% of planned data-center projects could face delays if grid risks are not addressed. In advanced economies, transmission lines can take four to eight years to build, and wait times for key components such as transformers and cables had doubled in the three years preceding that report. These are dated conditions from the 2025 analysis, not permanent limits.
The 2026 update notes that some US developers are advancing on-site natural-gas projects while grid connections are slow. On-site generation can provide interim capacity, but it does not eliminate transmission, fuel, emissions, permitting or long-term grid-planning constraints.
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The physical electricity mix serving a data center depends on its location and the regional grid. The IEA’s 2025 estimate of the global physical mix consumed by data centers was approximately 30% coal, 27% renewables, 26% natural gas and 15% nuclear.
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| Source in the IEA’s 2025 global estimate | Approximate share of physical electricity consumed | Context |
|---|---|---|
| Coal | 30% | Particularly significant where coal dominates the local grid |
| Renewables | 27% | Includes generation physically serving facilities; output varies by hour |
| Natural gas | 26% | The largest current source in the United States in the IEA’s regional description |
| Nuclear | 15% | More important in some regions; the IEA expects its role to grow after 2030 |
A power-purchase agreement or renewable-energy certificate is a contractual procurement arrangement. It does not mean that renewable electrons physically reach a facility at every hour. The table above describes the physical mix associated with consumption, not a company’s contractual claims.
In the IEA’s 2025 base case, renewables meet nearly half of the increase in data-center demand through 2030. Coal and natural gas together meet more than 40% of the additional demand. The balance differs by region: natural gas is the largest current source in the United States, while coal is dominant in China. Planned nuclear projects and other additions could matter more after 2030, but those are outlook assumptions rather than current supply.
Why forecasts differ
Electricity demand is not determined by the number of AI models alone. The IEA’s sensitivity cases vary assumptions about AI adoption, hardware and software efficiency, and energy-system bottlenecks. Its 2035 range runs from about 700 TWh in a Headwinds case to more than 1,700 TWh in a Lift-Off case. Those figures are scenarios, not confidence intervals or promises.
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- AI adoption: Faster deployment of agents, multimodal systems and industrial applications raises accelerator demand; slower commercialization lowers it.
- Efficiency: Better chips, model compression, cooling and utilization can reduce electricity per computation.
- Supply chains: Shortages of accelerators, memory, transformers, cables or generators can delay projects.
- Grid connections: A completed building cannot operate at full capacity without transmission and distribution access.
- Energy availability and cost: Local prices, permitting and reliability shape where developers build.
- Workload location: More inference at the edge or in smaller regional facilities could change the geography and timing of demand.
The 2026 central projection remains close to the previous trajectory, but the update emphasizes near-term bottlenecks and possible upside after 2030 if those constraints ease. A responsible headline therefore says demand is rising rapidly but uncertain, rather than assigning a single inevitable path.
What to watch when evaluating an electricity claim
- Check the report year and baseline. “415 TWh in 2024” and “485 TWh in 2025” come from different IEA editions.
- Separate measured or estimated historical consumption from a forecast for 2030 or 2035.
- Ask whether a number covers all data centers, only AI-focused facilities, or only accelerated servers.
- Distinguish total electricity use from the contribution to electricity-demand growth.
- Check whether a power mix is physical generation serving the site or a contractual procurement claim.
- Look at geography. A small global percentage can still require a new substation or transmission project in one region.
The practical takeaway
AI data centers consume electricity primarily because they run more and denser accelerator hardware, then consume additional power to store and move data, remove heat and maintain uninterrupted operation. The latest IEA central outlook places the sector near 950 TWh in 2030, but that number is conditional on adoption, efficiency, equipment supply and grid construction. Renewable generation is expected to supply a large share of growth, while fossil fuels remain important in current use and near-term additions. For communities and utilities, the decisive issue is often not the global percentage but whether local networks can connect a concentrated, rapidly growing load on the required schedule.
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