Key Questions on Energy and AI

Source: International Energy Agency · 2026-04-16

The largest technology companies are contributing to a surge in data centre investment, as their capital expenditure exceeded USD 400 billion in 2025 – and is expected to jump by another 75% in 2026. Capital expenditure of just five technology companies is now larger than global investment in oil and natural gas production. Many jurisdictions are seeing project pipelines accelerate dramatically, although not all projects will come to fruition. Those that are moving forward are doing so at pace: the IEA’s unique satellite-based tracking shows that “artificial intelligence (AI) factories” – cutting-edge data centres specifically designed for AI – have more than tripled in capacity in the past 18 months. Meanwhile, the capabilities of AI are improving quickly, increasing the likelihood that it will reshape economic growth, innovation and competitiveness and disrupt established industries and jobs.

Measured per individual task, the energy efficiency of AI is improving at a rate unprecedented in energy history. 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. Simple text queries now typically consume less electricity than running a television over the same period of time. If all conventional internet searches were performed with simple AI text queries, it would consume less than 4 terawatt-hours (TWh) of electricity annually, equivalent to less than 1% of total data centre consumption today.

However, new energy-intensive AI applications are increasingly being launched and used, such as those for video generation, reasoning and agentic tasks. 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 global electricity demand of data centres – the critical infrastructure for training and running AI models – grew by 17% in 2025, in line with IEA projections. Electricity consumption from AI-focused data centres grew even faster, surging 50% in 2025. While there are no comprehensive statistics on the frequency and depth of AI usage around the world, major model providers reported a threefold increase in active users and a fivefold increase in revenue over the past year, highlighting the rapid growth of demand.

The speed of the AI revolution is increasingly contrasting with the speed of the physical, social and economic systems that underpin it. Bottlenecks across energy supply chains and advanced chip manufacturing have tightened since our last report. Planning and regulatory systems are being stretched by the wave of project applications for data centres, amid a broader trend of rapid load growth and electrification. Social acceptability is also a growing issue, as communities push back against data centre projects, and concerns about affordability and environmental impacts rise. Essential elements within the IT industry are currently facing limitations; notably, a shortage of high-bandwidth memory – integral to AI chip production – has developed over the past six months and is anticipated to persist through at least the end of 2027.

Data centre investments have grown too large to be funded from company balance sheets alone, and large amounts of funding from capital markets will be critical for their buildout. As a result, the pace of data centre growth, and the resulting increase in energy consumption, will be sensitive to market sentiment, including expectations for returns on investment in data centres and AI deployment, as well as to broader macroeconomic and financing conditions. Understanding the energy implications of AI therefore also means following closely the technology’s economic trajectory.

The central projection for electricity demand from data centres remains close to the trajectory set out in the IEA’s 2025 report. Our updated projections see electricity consumption from data centres roughly doubling from 485 TWh in 2025 to 950 TWh in 2030, accounting for around 3% of global electricity demand by that date. Electricity consumption from AI-focused data centres grows much faster than overall data centre electricity consumption, tripling in this period. Bottlenecks across the value chain, however, are reducing the likelihood of more aggressive near-term scenarios, despite booming investment and surging project pipelines.

Constrained by slow grid connections, data centre developers in the United States are pushing forward projects with onsite natural gas-based power generation. Satellite tracking of these projects indicates that around one-fifth have started land clearing or construction. This highlights that onsite gas power is an emerging solution, with key design, supply chain, regulatory and financial questions remaining. New IEA analysis shows that providing reliable onsite gas-fired electricity to meet critical and variable data centre load requires overbuilding onsite generation infrastructure by 30% to 70% relative to demand.

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. 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.