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U.S. data centers used an estimated 176 terawatt-hours (TWh) of electricity in 2023, about 4.4% of total U.S. electricity use. The U.S. Department of Energy’s 2024 report projected a wide range—325 to 580 TWh—in 2028. Those totals cover data centers overall, not AI alone: AI is one driver among several, and the reports do not isolate its share.
What the 2024 DOE report found
The Department of Energy’s December 20, 2024 announcement summarized a Lawrence Berkeley National Laboratory analysis of U.S. data-center energy use from 2014 through 2028. It reported 58 TWh of use in 2014 and an estimated 176 TWh in 2023. For 2028, the report estimated a range of 325–580 TWh, equivalent to approximately 6.7%–12% of total U.S. electricity use.
The range matters. The upper figure is not a single-point prediction, and the national estimate should not be read as a forecast for a particular state, utility, or data center. The announcement describes AI applications as one of several factors contributing to demand growth; it does not attribute the entire increase to AI.
How the 2025 update changes the outlook
A later Lawrence Berkeley National Laboratory update extends the outlook through 2030 and gives a reference-case estimate of data centers using 11.8% of total U.S. electricity by that year. Its sensitivity scenarios are 9.5% and 15.3%. The update also estimates a 14% increase in U.S. data-center electricity use from 2023 to 2024 and a 21% compound annual growth rate for reference-case energy consumption further out. These are estimates in the update, not final measured totals. See the 2025 update and publication page.
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The 2024 and 2025 outlooks use different forecast horizons and present different metrics: the earlier announcement gives TWh totals and shares through 2028, while the update emphasizes a 2030 share, a reference case, and sensitivity scenarios. They should not be treated as directly interchangeable without comparing the underlying definitions and assumptions.
What the uncertainty ranges mean
The 2025 update describes sensitivity scenarios ranging from 11% below to 21% above its reference case, with compounded variation that could be roughly 20% below to 30% above. These are uncertainty ranges tied to assumptions, not confidence intervals unless the report defines them that way. They show why a scenario estimate is not a guaranteed outcome.
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How much electricity do AI data centers use?
The cited national figures do not answer that question precisely. They cover data centers overall and do not provide a separate total for facilities or workloads devoted to AI. It is accurate to say that AI applications contribute to rising demand; it is not supported by these figures to label all projected data-center electricity use as AI consumption.
Then-Secretary of Energy Jennifer M. Granholm framed the broader context in DOE’s 2024 announcement: “The United States has seen an incredible investment in artificial intelligence and other breakthrough technologies over the last decade and a half, and this industrial renaissance has created greater demand on our domestic energy supply,” The statement is from the announcement, rather than a finding quoted from the technical report.
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Why data-center growth can create local grid challenges
A national share does not tell a utility exactly where or when new demand will arrive. DOE notes that data-center loads are growing rapidly, vary by region, may be constrained by latency-related siting needs, and often require firm power continuously. These characteristics can make local planning difficult, but they do not mean every community or grid faces the same effect.
DOE describes a portfolio approach to meeting demand, including clean-energy resources, grid resources, and flexibility. Efficiency is another part of the response: DOE’s Federal Energy Management Program says its Data Center Profiler is an early-stage tool for estimating power usage effectiveness. That can help assess facility efficiency; it does not by itself resolve the wider question of how regional electricity supply will keep pace with new loads.
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