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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchAI data centers use large amounts of electricity because they run power-hungry accelerated computers around the clock, often at high density, and must also power the cooling and electrical systems that support them. Operators can reduce the energy needed for computing and coordinate supply, storage, and flexible demand—but no single measure solves every site’s needs.
How much electricity do data centers use?
The International Energy Agency (IEA) estimated that data centers worldwide used about 415 terawatt-hours (TWh) of electricity in 2024, or roughly 1.5% of global electricity consumption. In its 2025 base-case scenario, the IEA projected global data-center use would reach about 945 TWh in 2030. That is a scenario, not a guaranteed outcome: the IEA’s pathways vary with AI adoption, efficiency, and energy-sector constraints. IEA, “Energy demand from AI – Energy and AI” (2025).
AI is an important driver of the projected increase. In that same IEA base case for 2024–2030, electricity use by accelerated servers—equipment used mainly for AI workloads—was projected to grow by about 30% a year and account for almost half of net growth in data-center electricity consumption.
These figures measure energy, not instantaneous power. A facility’s power demand is commonly described in megawatts (MW); electricity consumed over time is measured in megawatt-hours (MWh) or, at a larger scale, TWh. A high peak demand and a large annual energy total are related, but they are not interchangeable measures.
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Why does AI computing need so much electricity?
Accelerated servers draw substantial power
AI training and inference rely on accelerated servers designed to perform intensive computations. Adding more of these servers, and packing them into a smaller area, raises a facility’s power density: more electricity must be delivered to each part of the building. The actual load depends on the equipment, workload, and how intensively the servers are used.
Cooling and electrical infrastructure add to the load
The computing equipment is not the entire bill. Cooling removes heat produced by servers, while power systems distribute electricity and support facility operation. In the IEA’s 2024–2030 outlook, cooling and other infrastructure account for about one-fifth of the net increase in data-center electricity consumption. Cooling’s share varies substantially by facility: the IEA gives a range from about 7% in efficient hyperscale data centers to more than 30% in less-efficient enterprise facilities. Those figures are not a universal share for every data center. IEA, “Energy demand from AI – Energy and AI” (2025).
Efficiency therefore matters both inside the server and across the facility. Better-performing hardware, software that uses computing resources more effectively, and more efficient cooling can reduce electricity use for a given amount of computing service. How much they save depends on the site and workload.
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Why can a modest global share create a local grid problem?
A global percentage can obscure where demand lands. Data centers are concentrated in particular locations, and a large facility can become a major new load for the local electricity system even when data centers account for a modest share worldwide. If projects grow faster than generation, transmission, or local connections can be built, operators may face delays or constraints.
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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesThe IEA has identified grid connection delays and shortages of equipment such as transformers among the factors that can slow data-center growth. Planning and construction take time, so coordinating the schedules for new facilities, power supply, and grid upgrades is part of managing demand—not a substitute for managing the electricity those facilities consume. IEA, “Executive summary – Energy and AI” (2025); IEA, “Data centre electricity use surged in 2025…” (2026).
The pace is also changing: the IEA reported that global data-center electricity demand rose 17% in 2025. That is a reported year-over-year increase, not a forecast for every subsequent year. Demand estimates should be read with their publication date and scenario assumptions in mind. IEA (2026).
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What can operators and grid planners do?
Different measures address different problems. Efficiency reduces the energy needed for computing; procurement and generation secure supply; batteries shift energy or buffer short-lived swings; and demand response changes when or how much a facility draws under agreed conditions.
| Approach | What it can do | Key limits or trade-offs |
|---|---|---|
| Efficiency improvements | Reduce electricity per unit of computing service through hardware, software, cooling, and facility operations. | Savings vary by workload, equipment, and facility; upgrades and operational changes have implementation costs and timelines. |
| Power procurement, including renewable PPAs | Contract for electricity supply and support investment in generation. | A power purchase agreement does not by itself mean the data center receives local renewable electricity in every hour. Geography, contract terms, and hourly matching matter. |
| Onsite generation | Add electricity supply close to the facility. | Reliability, fuel, emissions, ramping capability, permitting, and cost matter. The IEA notes technical and financial hurdles for onsite gas projects. |
| Battery storage | Buffer short-term changes in demand or shift electricity use across time; it may also help a facility respond to grid needs. | Value depends on battery power and duration, operating arrangements, cycling, and incentives. A battery does not automatically reduce total energy use or grid costs. |
| Demand response or a non-firm connection | Allow a facility to reduce or shift some demand under specified grid conditions, potentially easing connection constraints. | Terms determine notice, curtailment frequency, compensation, and which workloads can move. Limits must fit the facility’s service requirements. |
| Coordinated grid investment | Align new data-center connections with generation, transmission, and equipment upgrades. | Planning, permitting, and equipment supply can constrain how quickly new capacity becomes available. |
Efficiency: use less electricity for the same service
Improving server, software, cooling, and facility efficiency attacks the amount of electricity required to deliver computing. It is distinct from securing more electricity: a power contract can help cover a load, but it does not make the computing itself more efficient. The IEA’s projections show that assumptions about efficiency materially affect estimates of future demand. IEA (2025).
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Procurement and onsite supply: secure electricity
Operators can contract for electricity through power purchase agreements (PPAs) and pursue new sources of supply. The IEA reported that technology companies accounted for around 40% of corporate renewable PPAs signed in 2025. This is a share of contracts signed that year; it is not a measure of data-center electricity supplied by renewables, nor proof of hourly, local matching. IEA (2026).
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Onsite generation can place supply near a facility, but it brings its own engineering, fuel, emissions, permitting, and financial questions. The IEA has highlighted technical and financial hurdles for onsite gas projects, so onsite generation should not be treated as a simple or universal solution. IEA (2026).
Storage and flexible demand: respond to timing
Some AI facilities can see rapid swings in electricity demand. The IEA says such swings can stretch the technical capabilities of onsite gas plants and identifies onsite batteries as a potentially important buffer. Whether a battery helps the wider grid depends on how it is operated and incentivized; installing one alone does not guarantee lower total consumption or system costs. IEA (2026).
Demand-response programs and non-firm connection agreements can make some load reducible or shiftable at specified times. In exchange for possible connection or grid-system benefits, the operator needs to accept defined limits on service—such as when curtailment can occur and how much load must be reduced. The workload’s flexibility and the agreement’s terms determine whether that trade-off is practical. These arrangements are not the same as efficiency: they change the timing or availability of demand rather than necessarily reducing the energy needed for a completed workload.
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What the numbers do—and do not—say
Regional figures should not be blended with global totals. For example, the U.S. Department of Energy estimated that data centers consumed about 4.4% of U.S. electricity in 2023 and projected a range of 6.7%–12% for 2028. These are U.S.-specific figures from a 2024 report, with a projection range for a different reference year; they are not directly comparable to the IEA’s global 2024 estimate without keeping geography and year in view. U.S. Department of Energy (2024).
Backup generators and uninterruptible power supplies (UPS) are primarily reliability equipment, not routine demand-management tools. They are generally intended to keep service running through outages or power interruptions, rather than to reduce a data center’s normal electricity use. IEA, “Executive summary – Energy and AI” (2025).
There is no single best mix for every facility. The useful choices depend on its location, workload and load profile, grid constraints, service commitments, and the time needed to build supply or connections. Efficiency, procurement, storage, flexibility, and grid investment solve related but different parts of the problem.
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