Surge in AI usage, new apps overwhelm energy efficiency: IEA

The improvements in artificial intelligence (AI) energy efficiency per individual task is being overshadowed by the surge in the number of users and launch of energy-intensive AI applications, according to the International Energy Agency (IEA).

The net effect in the IEA's new report Key Questions on Energy and AI reveals that electricity consumption from data centres will roughly double from 485 Terawatt-hour (TWh) in 2025 to 950 TWh in 2030.

On the one hand, software and hardware advances have "resulted in the energy use per AI task dropping by at least an order of magnitude annually in recent years," the IEA explained, pointing to simple text queries that now typically consume less electricity than running a television over the same period.

However, new energy-intensive AI applications, such as those for video generation, reasoning and agentic tasks, are increasingly being launched and used.

"These kinds of tasks can consume hundreds or thousands of times more energy per query than simple text generation. The energy demand of AI is therefore the result of three rapidly evolving and uncertain trends: improvements in efficiency, surging uptake, and changing model capabilities, which can unlock new and, in many instances, far more energy-intensive use cases," the IEA said.

During 2025, global electricity demand of data centres - the critical infrastructure for training and running AI models - grew by 17%, which was in line with IEA projections. Electricity consumption from AI-focused data centres grew even faster at 50%.

While there are no comprehensive statistics on the frequency and depth of AI usage around the world, the IEA said major model providers reported a "threefold increase in active users and a fivefold increase in revenue over the past year."

On a positive note, the technology sector might still be an energy taker, it is increasingly becoming an energy maker.

As an example, the IEA points out the sector is a major driver of renewables procurement, accounting for about 40% of all corporate renewables power purchase agreements (PPAs) signed globally in 2025.

The report also highlights the "wide range of projections of the impact of AI on GDP."

"Stronger economic growth from AI does not translate one-to-one into higher energy demand. It is concentrated in knowledge-intensive services and high-income countries, where the elasticity between energy demand and economic activity is lower," the report read.

"Estimates show that, depending on the scale of uptake, an AI-driven growth boost could raise the level of global energy demand by between 1-4% in 2035 compared with trends without this AI boost."

Such effects appear to be concentrated in advanced economies, such as the US.

"In our analysis, the impact of energy policies and energy technology developments on energy demand is much larger than the potential impact of an AI-driven economic growth boost," the IEA said.

IEA executive director Fatih Birol commented: "Now, we see that while AI is still an energy taker, it is also becoming an energy maker - driving forward innovative solutions like next-generation nuclear reactors, flexible data centres and long-duration energy storage."

"To help countries that seize on this opportunity to modernise their energy systems, and to tackle bottlenecks and other concerns associated with AI's rapid growth, collaboration between policymakers and the energy and tech sectors remains crucial."

The agency will soon launch a new platform for government and industry to regularly discuss energy and AI issues.