AI servers will consume more power than all conventional data center hardware combined by 2027 — global data center electricity consumption set to grow by 26% this year, Gartner forecasts

Global data center electricity consumption will grow 26% in 2026 to reach 565 terawatt-hours (TWh), up from 447 TWh in 2025, according to a recent Gartner forecast that names power availability as a binding constraint on AI expansion. Worldwide power demand is set to rise 27% to 132 GW over the same period, up from 104 GW in 2025, with consumption projected to exceed 1,200 TWh by 2030. The gigawatt figure measures peak capacity that has yet to be built, permitted, and connected, while the terawatt-hour figure measures the electricity actually drawn over the year. Both, however, are climbing faster than utilities can add supply.

“Surging demand for compute-intensive AI workloads is driving unprecedented data center power growth, while AI capacity is now constrained by power availability, making data center power security the new battle ground for scaling and protecting margins in the global AI race,” said Gartner’s Direct Analyst Linglan Wang.

AI-optimized servers consumed about 95 TWh worldwide in 2025 and will draw 175 TWh in 2026, an increase of roughly 84%. Gartner expects that figure to reach 258 TWh in 2027, the point at which AI-optimized hardware will consume more electricity than conventional servers for the first time. By 2030, AI-optimized servers are forecast to account for close to half of all data center power consumption.

Conventional servers are effectively flat by comparison. They grew less than 1% in 2025 and are projected to rise 1.2% in 2026 to around 195 TWh, reaching 200 TWh in 2027. Gartner estimates AI-optimized servers will make up 31% of total data center power consumption in 2026, up from roughly 20% a year earlier. Cooling, of course, represents a growing share of the total, with electricity used by cooling systems forecast to climb 22.6% in 2026 to 195 TWh, reflecting the thermal load of denser AI racks and continued capacity expansion.

The U.S. accounts for about 204 TWh of the 565 TWh total in 2026, or 36% of worldwide consumption. Of that U.S. figure, dedicated AI data centers consume roughly 68 TWh, or one-third of the national total, while non-AI data center demand in the country has grown only marginally over the same period.

Regional grids are already feeling the strain, and more than 75 data center projects worth $130 billion were blocked in the first months of 2026 amid opposition over power and water costs, while some operators have turned to on-site gas generators to bring capacity online without waiting for grid connections. In Virginia, one county asked employees to conserve power as data center demand pushed utility rates higher.

In its report, Garner warns that grid supply will be insufficient to meet demand once consumption passes 1,200 TWh by 2030, a shortfall that will affect all data center users, not just AI operators. The forecast accounts for parts and supply shortages, delayed or cancelled projects, and geopolitical disruption, including conflict involving Iran. Wang said infrastructure and operations leaders should prioritize efficiency upgrades, secure grid access, and invest in high-efficiency cooling and edge computing to manage the constraint.

Hyperscalers have moved in the same direction, with Meta having signed deals for more than 6GW of nuclear power to supply its upcoming data centers, and one firm repurposing retired U.S. Navy reactors for an AI site in Tennessee. Those projects will take years to deliver, with recommissioned nuclear plants and the earliest small modular reactors not expected online until 2028 or later, leaving power availability as a near-term limitation on the seemingly unstoppable AI build-out.