AI and data centre electricity use continue to surge, IEA finds

The report, highlighting how any discussion of AI must go hand in hand with that of data centres, finds that while electricity demand from data centres increased by 17% in 2025, that of AI-focused data centres soared by 50% – both well outpacing growth in global electricity demand of 3%. 

The driver is data centre investments, with the capital expenditure of the five largest technology companies – Amazon Web Services, Google, Meta, Microsoft and Equinix – having surged to more than $400 billion in 2025 and set to jump by a further 75% in 2026. 

With software and hardware advances, the power consumption per AI task is declining rapidly, by at least an order of magnitude annually in recent years – a rate believed to be unprecedented in energy history. 

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However, more people are using AI and energy-intensive applications, such as AI agents, are on the rise. As a result, while the total electricity consumption of data centres is projected to double by 2030, from 485TWh to 950TWh – reaching approximately 3% of global demand – the power use from those focused on AI is poised to triple to 465TWh to approach that of the conventional centres. 

At the same time, AI deployment is increasingly coming up against a range of physical bottlenecks, limiting the rate at which data centres can expand in the near-term, the IEA highlights. 

Bottlenecks and challenges

Supply chains for energy technologies such as gas turbines and transformers, as well as for advanced chips and IT components, have tightened over the past year. The growing pipeline of data centre projects is also straining planning and regulatory systems, holding up grid connections and other necessary approvals. 

The IEA comments that to solve the energy challenges at hand, the tech sector is adopting new approaches. It accounted for around 40% of all corporate power purchase agreements for renewables signed in 2025 and is also now a major source of momentum for the nuclear and advanced geothermal industries.  

For example, the pipeline of conditional offtake agreements between data centre operators and SMR nuclear projects has grown from 25GW at the end of 2024 to 45GW today, which is also indicative that such momentum behind AI could accelerate the commercialisation of new energy technologies.   

Data centre developers are also advancing a large number of projects with onsite natural gas-based power generation, largely in the US. Many of these projects remain in their early stages, the IEA reports from satellite-based tracking data, and is indicative of the technical and financial hurdles that need to be overcome.  

A key challenge is that AI data centres have rapid and large swings in demand and meeting their power needs reliably can stretch the technical capabilities of onsite gas plants. Hence, onsite battery storage is also becoming a critical technology for the next generation of AI data centres, also opening the way for flexibility provision. 

“The IEA was early in recognising that there is no AI without energy – and that countries that provide secure, affordable and rapid access to electricity will be one step ahead,” said IEA Executive Director Fatih Birol. 

“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.” 

To this end, the IEA has announced the forthcoming launch of a new platform for government and industry to discuss energy and AI issues. 

Looking ahead

Other findings of the report, Key question on Energy and AI, include that AI is boosting productivity in some sectors and may be critical for global industrial innovation and competitiveness. For example, proven AI applications can help firms in energy-intensive industries reduce their energy costs by 3 to 10 percentage points.  

However, the energy sector as a whole is not yet taking full advantage of AI’s potential, with the lack of sufficient digital skills and the availability of data emerging as key barriers to adoption. 

Looking ahead, the supply chain ramp-up is likely to be tested. Consider, between 2020 and 2025 the power density of AI servers increased by 11 times and by 2027 a further four-fold increase is expected, requiring key electronic technologies such as power electronics and transformers. 

With some of these technologies depending on critical inputs from a small number of producers, notably China, care is needed to ensure that the supply chains are diverse and resilient. 

The IEA concludes with three recommendations for leveraging AI deployment in the energy sector and minimising the impact of data centres on electricity systems: 

• Proactive management of data centre project pipelines and electricity sector investment can support adequate and reliable electricity for the sector without adversely affecting prices. 
• Approaches that promote electricity system flexibility can help accelerate grid connections and ensure electricity affordability. 
• Removing barriers to AI adoption in the energy sector can ensure AI is leveraged to enhance energy security and sustainability.