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Data-center electricity forecasts are rising, but there is no single number that answers how much power these facilities will use. The International Energy Agency’s global outlooks and Lawrence Berkeley National Laboratory’s U.S. estimate use different geographies, forecast vintages and methods. Their figures should be treated as projections with inspectable assumptions—not interchangeable measurements or proof that every proposed facility will be built.
What do the latest estimates actually say?
The International Energy Agency (IEA) and Lawrence Berkeley National Laboratory (LBNL) offer useful reference points, but they do not measure the same system. The IEA’s figures are global; LBNL’s are for the United States. The IEA’s 2025 report and its updated outlook accessed in 2026 also have different reference years.
| Source and outlook | Geography and scenario | Projected electricity consumption |
|---|---|---|
| IEA, Energy and AI (2025) | Global, 2025 Base Case | 415 TWh in 2024, about 1.5% of world electricity consumption; around 945 TWh in 2030. |
| IEA, updated outlook accessed in 2026 | Global; the executive summary says its central projection remains close to the 2025 report’s trajectory. | 485 TWh in 2025 and around 950 TWh in 2030. The page material retrieved did not establish a publication date. |
| LBNL, 2025 U.S. update | United States, Reference Case | 649 TWh in 2030; LBNL gives a compounded uncertainty range of 521–843 TWh. Its public summary expresses the central estimate as 11.8% of U.S. electricity, with a 9.5–15.3% range. |
These numbers are not contradictory readings of a meter. The 2025 IEA report estimated 415 TWh for 2024 and around 945 TWh for 2030; the IEA’s later-accessed outlook estimates 485 TWh for 2025 and around 950 TWh for 2030. Each reflects its own report vintage, starting year and inputs. LBNL’s U.S. 2030 Reference Case is a separate national estimate, not a competing global forecast.
Percentages need their denominator attached. The IEA’s roughly 1.5% figure is data-center electricity as a share of global electricity consumption in 2024. LBNL’s 11.8% central estimate and 9.5–15.3% range refer to U.S. electricity in 2030 under its update’s estimate and scenarios. A large national share is not evidence that every region faces the same impact: the IEA notes that data-center capacity and demand are geographically concentrated.
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Why estimates can move—and why they differ
A forecast is a model of future facilities and equipment, not a direct count of electricity already consumed. The IEA has cautioned that there is substantial uncertainty about data-center consumption both now and in the future. A change between report editions may reflect revised inputs or assumptions as well as changes in expected demand; it should not automatically be described as new measured consumption.
LBNL’s 2025 estimate makes some of its modeling inputs visible. Its method combines equipment-shipment data, device electricity models, cooling simulations and facility information. The report also describes sensitivity cases that test alternative data and industry feedback. That approach gives policymakers and readers specific assumptions to inspect, while leaving uncertainty about what the future build-out and operation will look like.
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To compare two forecasts responsibly, first establish what each one is counting:
- Geography and date: Is the forecast global, national or regional? When was it published, and what is its baseline year or data cutoff?
- Measure and scenario: Does it estimate annual electricity consumption in TWh or peak power demand? Is it a central, reference, high-demand or other scenario?
- Facilities included: Does it count operating sites only, or also projects that are announced, queued for grid connection, contracted, financed or under construction?
- Technology and operation: What does it assume about equipment shipments, server utilization, idle power, cooling and efficiency gains?
- Percentage denominator: If a share is quoted, is it a share of global or U.S. electricity, and for which year?
A TWh forecast for annual consumption cannot be compared directly with a peak-demand figure. Nor should a queued project be silently treated as equivalent to an operating facility. A credible comparison labels those differences rather than collapsing them into a headline number.
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Why a global forecast does not answer a local grid question
The IEA’s estimate that data centers used about 1.5% of global electricity in 2024 describes an aggregate. It does not show how much load a particular utility, transmission corridor or community must serve. Because capacity and demand are concentrated geographically, a modest global share can coincide with substantial local planning pressure.
There is also a gap between planned demand and demand that materializes. In its 2025 analysis, the IEA estimated that around 20% of planned data-center projects could be at risk of delay if grid risks are not addressed. It reported that transmission lines can take four to eight years to build in advanced economies and that waits for critical grid components have lengthened. Those system constraints make timelines uncertain; they do not, on their own, establish that any particular project is speculative or will be cancelled.
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Utilities and planners therefore need to distinguish among the load they already serve, projects with credible commitments and proposals still subject to financing, construction or grid access. Forecasts are useful for preparing for possible demand, but if every proposal is counted as certain, the estimate may overstate what arrives on a particular schedule. If plausible projects are omitted, it may understate future needs. The public should be able to see how a forecast handles that uncertainty.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Who should substantiate the assumptions?
Responsibility is shared. Forecast authors should disclose their methods and scenario boundaries. Data-center developers and operators are best placed to substantiate project status, expected power needs and timing. Utilities should explain how they translate applications and commitments into load forecasts and infrastructure plans. Regulators and public authorities can set reporting rules, review assumptions and make relevant data available without treating every early-stage proposal as a guaranteed customer.
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Existing reporting and policy examples show ways to improve scrutiny, though they differ in scope and legal basis:
- European Union: The IEA’s 2024 Electricity report describes energy-use and emissions reporting by data-center operators beginning in 2024. That is an accountability mechanism for reported performance, distinct from a forecast of future demand.
- United States: The IEA describes Energy Act of 2020 provisions for studies, metrics, good practices and public reporting of historical data-center energy and water use. Historical reporting can help establish a baseline, but it does not by itself validate a particular utility’s forecast of future projects.
- Texas: The Associated Press reported that Texas lawmakers enacted a measure requiring developers to disclose whether they have requested power elsewhere in Texas and to demonstrate substantial financial commitment to a site. That account supports the broad policy description; the detailed legal duties should be checked against the statute and current implementation before being stated more specifically.
Reporting is most useful when it allows an outside reviewer to distinguish observed consumption from forecasts, and firm commitments from less certain projects. Aggregate publication can support oversight while avoiding disclosure of sensitive site-level or commercial information where the rules permit that protection.
What transparent forecasting should include
An estimate should be accompanied by enough information for a reader to understand what would make it rise or fall. At minimum, the publisher should identify the geography, publication date, baseline year, forecast horizon, scenario, metric and denominator. It should explain the facility categories counted, key equipment and operating assumptions, and how efficiency improvements are treated.
It should also show how project maturity affects the total. A forecast can report a central case alongside sensitivity ranges for uncertain inputs and project delivery, explain how it handles projects that are delayed or abandoned, and update its assumptions when actual consumption or development status changes. Ranges such as LBNL’s 521–843 TWh uncertainty range are informative only when their geography, year and scenario remain attached to them.
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That standard does not require one agency to certify a single correct number. It requires the institutions using estimates—in particular utilities, planners and public authorities—to say what the number represents, who supplied the underlying information, how uncertainty is handled and what evidence would trigger a revision. Without that, a forecast can look more certain than the projects and assumptions beneath it.
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