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Data centres use electricity to run servers, storage and networking equipment—and to keep that equipment cool and reliably powered. Water can be consumed directly for cooling or indirectly when power plants generate the electricity a facility uses. Land is needed for buildings and supporting infrastructure, but the sources cited here do not establish a consistent global total for data-centre land use. The amounts vary with facility design, climate, workload, local electricity supply and the boundary used to count each resource.
Why data centres use so much electricity
Every digital service that stores or processes information depends on physical equipment. Servers and accelerators perform computation; storage devices hold data; and networking equipment moves it. Those devices draw electricity while operating. Power-conversion equipment, cooling, lighting and other facility systems add to the site’s demand.
Almost all the electricity used by computing equipment ultimately becomes heat. If that heat is not removed, equipment can overheat or fail, so data centres use cooling systems alongside power conditioning and, often, backup systems to support continuous operation. The International Energy Agency (IEA) estimates that global data-centre electricity consumption was 415 terawatt-hours (TWh) in 2024, about 1.5% of the world’s electricity use. Its 2025 base case projects consumption of about 945 TWh in 2030; that is a scenario, not a guaranteed outcome. IEA, Energy and AI: Energy demand from AI.
Consumption and generation figures are not interchangeable
The IEA also describes electricity generation serving data centres, estimating 460 TWh in 2024 and projecting more than 1,000 TWh in 2030. That is a separate measure from its estimate and projection of data-centre electricity consumption. The figures use different accounting concepts, so they should not be combined into one forecast. IEA, Energy and AI: Energy supply for AI.
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Why cooling adds to electricity demand
Cooling takes electricity to move heat away from equipment, but its share of a facility’s use depends on the building and its systems. The IEA reports that cooling accounts for about 7% of electricity use in efficient hyperscale data centres, compared with more than 30% in less-efficient enterprise centres. These are examples at different ends of a range, not a universal percentage for every data centre. IEA, Energy and AI: Energy demand from AI.
Cooling technology and climate matter: a system that works well in one setting may not be the best choice in another. Facility efficiency matters too. This is why comparisons are most useful when they match the facility type, location, year and workload rather than treating all data centres as equivalent.
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Where data-centre water use comes from
Water use has two distinct boundaries. Direct, or site, water is used at the data centre, including in some evaporative cooling systems. Indirect, or source, water is consumed in producing the electricity that powers it. A water-use figure that counts only one boundary does not describe the other.
| Water boundary | What it counts | Why it varies |
|---|---|---|
| Direct (site) | Water consumed at the facility, including for evaporative cooling where used. | Cooling design, operating conditions and local climate affect use. |
| Indirect (electricity supply) | Water consumed in generating the electricity used by the facility. | It depends partly on the electricity sources serving the facility and their water intensity. |
There can be a trade-off between these boundaries. An air-cooled chiller may use no water at the facility while requiring more electricity than a water-cooled alternative. The indirect water impact of that extra electricity depends on the grid supplying it. The Lawrence Berkeley National Laboratory’s 2024 U.S. data-centre report discusses these system boundaries; its estimates are U.S.-specific and should not be presented as global totals. Lawrence Berkeley National Laboratory, 2024 United States Data Center Energy Usage Report.
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Why there is no universal water figure per workload
A 2025 review by Nuoa Lei, Jun Lu, Arman Shehabi and Eric R. Masanet found that workload-level water use varied by more than 10,000-fold across the conditions studied. The review identifies server efficiency and utilization, idle equipment, cooling system, facility efficiency, climate, electricity-generation water factors and equipment refresh cycles as relevant determinants. A single figure for water per query or per data centre would therefore be misleading unless its workload, location, cooling design and accounting boundary were specified. Lei et al., The water use of data center workloads: A review and assessment of key determinants.
Why data centres need land—and why local siting matters
Data centres need a physical site for buildings, servers, cooling equipment and other infrastructure. They also need access to substantial, reliable power and supporting connections. Location can be constrained by the need to serve users with suitable latency, while a large or rapidly growing electricity load can affect regional grids.
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The U.S. Department of Energy’s December 2024 summary of a national report said U.S. data-centre load growth had tripled over the prior decade and was then projected to double or triple by 2028. That was a projection made in 2024, not a current measurement or the latest forecast. It illustrates why the impact of a facility can be significant for its local power system even when global electricity shares appear modest. U.S. Department of Energy, DOE Releases New Report Evaluating Increase in Electricity Demand from Data Centers.
There is no consistent global land-footprint total established by the sources cited here. A land estimate would need to state what it counts: the building parcel, a larger campus, substations and transmission, power-generation sites, or a broader supply chain. Those boundaries describe different impacts, so a single universal land-per-data-centre figure would not be meaningful without a defined method.
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What makes resource use differ from one data centre to another
- Workload and utilization: the amount and type of computing performed, and how much installed equipment is actually in use, affect electricity demand and workload-level water estimates.
- Equipment and facility efficiency: server efficiency, power systems and cooling overhead influence how much electricity is needed for a given computing task.
- Cooling design and climate: these shape direct site-water use and the electricity required to remove heat.
- Electricity supply: the generation mix affects indirect water use, while the power available at a suitable location influences siting.
- Accounting boundary: electricity consumed at a facility is not the same measure as generation serving it; site water is not the same as water used in electricity generation; and a building parcel is not the same as land for associated energy infrastructure.
For a fair comparison, use the same geography, year, workload and accounting boundary. The cited sources do not provide one harmonized international dataset covering all these measures, so seemingly similar headline figures may not be directly comparable.
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