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Data centers power AI by feeding electricity to servers—often equipped with GPUs and other accelerators—that train and run AI models. They also use electricity for cooling, networking, storage, and backup systems. AI is pushing demand upward because more accelerated servers are being deployed, and each can draw substantial power; efficiency gains do not guarantee lower total consumption when demand for computing grows faster.
How a data center turns electricity into AI computing
A data center combines computing equipment with the power, cooling, and network systems needed to keep it operating. Electricity from the grid or another source passes through facility power systems to servers, storage, networking equipment, and cooling. Servers perform the calculations behind AI training and use; cooling carries away the heat those calculations produce. UPS batteries and backup generators help maintain operation when the normal supply is interrupted.
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Servers do most of the computing—and usually use the most power
Servers contain CPUs and may include specialized accelerators such as GPUs. These components process the operations needed to train AI models or answer requests from deployed models. The International Energy Agency (IEA) estimates that servers average around 60% of data-center electricity demand, but the share varies by facility.
Cooling, storage, and networking add to the load
Storage retains data, while networking equipment moves data within the facility and to users or other systems. IEA estimates put storage at around 5% of electricity use and networking at up to 5%. Cooling ranges from about 7% in efficient hyperscale facilities to more than 30% in less-efficient enterprise facilities. These are indicative estimates, not a fixed breakdown for every data center.
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The IEA captures that variation in its explanation of energy demand from AI: “The share of these different components in data centre electricity consumption varies greatly by type of data centre, depending on the nature and efficiency of the equipment they have installed.”
Why AI is increasing data-center electricity use
AI workloads have accelerated the deployment of high-performance servers built around accelerators. These systems increase computing capacity and power density—the amount of power concentrated in a given area—so facilities must supply more electricity and remove more heat.
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In its 2025 global Base Case, the IEA projected electricity consumption by accelerated servers to grow about 30% annually from 2024 to 2030, compared with 9% annually for conventional servers. Accelerated servers account for almost half of the projected net increase in global data-center electricity consumption in that scenario.
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A chip may perform more computation for each unit of electricity, but that does not ensure lower total electricity use. The 2025 U.S. report from Lawrence Berkeley National Laboratory (Berkeley Lab) says rising demand is driven primarily by both the number of accelerated servers shipped and their rated power. It also finds that computational demand grew enough to more than offset efficiency gains. In other words, if demand for computing expands faster than efficiency improves, total power use can go up.
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How much electricity data centers use—and what forecasts mean
Estimates need to be read with their geography, year, workload scope, and scenario attached. A global figure for all data centers is not an estimate of AI alone, and a U.S. forecast is not directly comparable to a global one.
| Estimate | What it describes |
| 415 TWh in 2024, about 1.5% of global electricity consumption | IEA’s 2025 estimate for all data centers worldwide, not AI alone. |
| About 945 TWh in 2030 | IEA’s 2025 global Base Case projection for data-center electricity consumption; a scenario, not a measured outcome. |
| 485 TWh in 2025, rising to roughly 950 TWh in 2030 | IEA’s 2026 global update. It projects data centers at around 3% of global electricity demand by 2030 and says electricity consumption from AI-focused data centers will triple over the period. |
| 649 TWh in 2030; 521–843 TWh across compounded uncertainty bounds | Berkeley Lab’s 2026 U.S. Reference Case and uncertainty bounds. Its bottom-up model considers equipment shipments, device power, cooling performance, facility types, and locations. This is U.S.-only, not a global estimate. |
| 17% growth in 2025 for data-center electricity demand; 50% for AI-focused data-center consumption | IEA’s global year-on-year growth figures in its 2026 update. |
The IEA’s 2025 and 2026 global outlooks put their 2030 headline figures close to one another, but they use different reference years and modeling updates. The forecasts remain scenario-dependent: equipment shipments, utilization, AI adoption, efficiency, and infrastructure constraints can all affect the outcome.
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Why data centers can strain local grids
A global share can look modest while the effect is substantial in particular places. Data centers tend to cluster, draw large loads, and often need reliable electricity around the clock. Location choices also reflect access to power and latency requirements. The IEA says this concentration can make grid integration more challenging; the U.S. Department of Energy (DOE) describes rapidly growing, regionally varying demand, large load increases, and the need for firm power as planning challenges.
Meeting that demand involves more than building power plants. The DOE’s discussion of rising data-center electricity demand identifies options including clean generation and storage, grid expansion and modernization, energy efficiency, demand flexibility, existing nuclear and hydropower, and changes to planning or tariffs. These are approaches under consideration, not guaranteed fixes or features of every facility.
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What supplies the electricity?
Data centers are not powered by one universal source. The supply mix depends on location and changes over time. In the IEA’s 2025 Base Case, renewables meet nearly half of the additional data-center electricity demand through 2030; natural gas and coal also contribute, while nuclear becomes more important toward the end of the decade and beyond. That scenario does not mean every facility uses the same mix, or that all data-center electricity is either clean or fossil-fueled.
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