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What makes a data center “AI” or traditional?
An AI data center runs equipment and workloads designed for tasks such as training or operating AI models. A traditional data center may support cloud services, storage, business applications or other computing. The categories can overlap: facilities may run mixed workloads, and the term “AI data center” does not by itself specify a facility’s size, energy efficiency or cooling system.
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A useful comparison separates the workload from the building and its operating conditions. A large, highly utilized AI facility can draw far more power than a smaller conventional one; an efficient hyperscale facility may also devote a smaller share of its electricity to cooling than a less-efficient enterprise facility. Nameplate capacity alone does not show how much electricity a site will actually use over time.
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How much more electricity does an AI data center use?
There is no single multiplier that applies to every AI-versus-traditional comparison. The International Energy Agency (IEA) gives an illustrative facility-scale contrast: traditional data centers commonly use 10–25 MW, while hyperscale AI centers can exceed 100 MW. These are representative categories, not measured averages for every facility, and they compare capacity in megawatts—not annual electricity consumption.
| Measure | Figure | What it describes |
|---|---|---|
| Traditional data-center capacity | Commonly 10–25 MW | Illustrative facility category in the IEA’s 2025 topic material; not an average for all traditional centers. |
| Hyperscale AI-center capacity | Can exceed 100 MW | Illustrative facility category in the IEA’s 2025 topic material; not a claim about every AI facility. |
| Global data-center electricity use | 415 TWh, around 1.5% of global electricity | IEA estimate for 2024, published in its 2025 analysis. |
| Global data-center electricity use | 485 TWh; up 17% during the year | IEA estimate for 2025, published in its April 2026 update. |
| AI-focused data-center electricity use | Up 50% during 2025; projected to triple from 2025 to 2030 | IEA’s April 2026 update; the growth and projection concern AI-focused centers, not all data centers. |
| Global data-center electricity outlook | Around 945 TWh in 2030 | IEA 2025 Base Case projection. |
| Global data-center electricity outlook | About 950 TWh in 2030 | IEA estimate in its April 2026 update. |
The two 2030 outlooks are separate projections published at different times, not one figure to combine or treat as a realized outcome. Both describe total data-center electricity use, while the 2026 AI-focused growth figures describe a subset. The IEA identifies accelerated servers, mainly associated with AI, as a major driver of expected growth; traditional servers and supporting infrastructure also contribute, and the projection includes growth across facility types.
Why a capacity figure is not an electricity bill
Megawatts (MW) describe power capacity or demand at a point in time; terawatt-hours (TWh) describe electricity used over a period. Actual annual consumption depends on how much computing equipment is installed and how intensively it operates, as well as the electricity used by cooling and other supporting systems. A comparison needs the same boundary and timeframe—for example, whole-facility annual electricity use rather than IT equipment alone.
Cooling is one reason a simple “AI uses X times more energy” claim can mislead. In its 2025 analysis, the IEA reports that cooling accounts for about 7% of electricity use in efficient hyperscale centers and more than 30% in less-efficient enterprise centers. Those figures compare efficiency and facility types; they are not a direct AI-versus-traditional ratio.
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Not necessarily in every comparison, and there is no established universal water-use ratio for AI-focused versus traditional data centers. Workload alone does not determine water demand. Cooling design, local climate and the electricity supply mix all affect a facility’s water footprint.
When evaluating a specific site, distinguish two kinds of water use:
- Water used at the facility: Ask what cooling method is proposed, where its water comes from, and how much is withdrawn versus consumed. These are different measures: water withdrawn may be returned to the source, while water consumed is not returned locally in the same form or timeframe.
- Water associated with electricity generation: Power plants serving the facility may also use water. This indirect water use depends on the generation mix and should not be confused with water used for on-site cooling.
Climate and watershed conditions matter as much as the headline consumption figure. The same cooling approach can have different implications in a water-abundant region and a water-stressed one. For a proposed facility, seek site-specific estimates that state the location, period, water source, metric and accounting boundary.
What do data centers mean for emissions?
Electricity-related emissions depend on the power generation serving a facility and on how the emissions are accounted for. The IEA’s 2025 analysis estimated about 180 million metric tons (Mt) of indirect electricity-related CO2 emissions from data centers. That estimate covers data-center workloads overall, including AI as a subset, and excludes emissions from backup power generation.
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A facility’s renewable-energy contract should not automatically be treated as identical to the electricity physically delivered to the site every hour. A meaningful comparison identifies the location, electricity mix and accounting method used, and explains whether backup generation is included. Without a shared boundary, emissions figures for two sites may not be comparable.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What can a new data center mean for local power bills and water supplies?
A facility can be a small share of global electricity demand and still be a significant new load in the local grid where it connects. The IEA reports that nearly half of US data-center capacity is concentrated in five regional clusters, and that data centers account for substantial shares of electricity use in some local markets. Global percentages therefore cannot settle the question of a particular community’s grid capacity or costs.
Whether a new load affects electricity prices depends on local conditions: available generation and grid capacity, when the facility draws power, required network investment and the policies that determine who pays. In a constrained system, a large new connection can require investment and raise questions about congestion, connection delays and cost allocation. Where supply exceeds demand or existing infrastructure is underused, added demand may improve its utilization. A price increase is possible, but not automatic; neither is the claim that a facility will have no effect.
Water impacts are similarly local. The relevant questions are whether the facility’s water source and cooling demand could strain a watershed, what water will be consumed rather than merely withdrawn, and whether other users face competing needs. A broad industry comparison cannot answer those questions for a specific town or utility area.
How to compare two specific facilities
For an apples-to-apples comparison, request the same measures, periods and boundaries from each operator or permitting document. Focus on these site details:
- Capacity and workload: What is the installed IT capacity, what workloads will run, and what level of utilization is expected?
- Electricity demand: What is expected peak demand and annual facility electricity use, including cooling and other supporting systems?
- Power supply: What electricity mix physically serves the site, and how does any renewable-energy claim relate to supply across different hours?
- Cooling and water: What cooling design is planned? What is the water source, and what are the expected withdrawal and consumption figures?
- Local conditions: Is the watershed water-stressed? How much grid headroom is available, and when could the facility connect?
- Infrastructure costs: What new generation or network investment is required, and how are those costs allocated among the operator, utility and other customers?
- Emissions boundary: Which electricity mix and accounting method are used, and are backup generators included?
The IEA’s 2025 report, Energy and AI, summarizes the tension: “There is no AI without energy; at the same time, AI has the potential to transform the energy sector.” That potential does not resolve the local trade-offs on its own: the outcome depends on the facility’s design, the power and water systems it connects to, and the terms under which new infrastructure is built.
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