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AI’s climate impact is growing, but the best available global figures measure data centres as a whole—not AI alone. The International Energy Agency (IEA) estimates that data centres used 415 terawatt-hours (TWh) of electricity in 2024, about 1.5% of global electricity use. The emissions from that power depend on how it is generated and where data centres connect to the grid.
How much electricity does AI use?
There is no reliable global total in the cited estimates for AI’s electricity use alone. The headline figures cover all data centre workloads, with AI as one part of the total. They are useful for showing the scale and growth of the infrastructure AI relies on, but should not be described as AI-only consumption.
The IEA’s 2025 estimate puts all data centre electricity consumption at 415 TWh in 2024, or about 1.5% of global electricity consumption. Its 2026 update says total data centre electricity demand grew 17% in 2025, while electricity consumption in AI-focused data centres grew 50%. The latter is a growth rate for AI-focused facilities, not a global AI-only electricity total. IEA: Energy demand from AI; IEA: Key Questions on Energy and AI, executive summary.
Those sources use different years and estimates: the IEA’s 2026 update gives 485 TWh for 2025, while its 2025 report estimated 415 TWh for 2024. Treat them as dated estimates, not a precise year-to-year measurement series. The IEA also cautions that there is substantial uncertainty about data centre consumption now and in the future.
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Does AI increase climate change?
AI contributes to climate change when the electricity used to train and run it causes greenhouse-gas emissions. The amount depends on the power supply: electricity from a more carbon-intensive mix generally has a greater emissions impact than electricity from a lower-carbon mix. The IEA estimated around 180 million tonnes (Mt) of indirect CO₂ emissions from data centre electricity in 2024. That estimate covers all data centre workloads, excludes emissions from backup power, and is not an AI-only figure. IEA: AI and climate change.
The global average also hides where electricity demand is added. In the IEA’s 2025 Base Case, renewables meet nearly half of additional data centre electricity demand through 2030, while natural gas and coal together meet over 40%. The power physically supplying a facility depends on its grid connection; a company’s contractual renewable-electricity claims are not the same thing as the local grid’s physical mix. IEA: Energy supply for AI.
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How fast could data centre emissions grow?
The IEA’s 2026 central projection puts total data centre electricity consumption at 485 TWh in 2025 and 950 TWh in 2030—roughly a doubling. These are data centre totals, not AI-only consumption, and a projection rather than a guaranteed outcome. Efficiency, AI uptake, model capabilities and energy-system bottlenecks can all affect the result. IEA: Key Questions on Energy and AI, executive summary.
Emissions projections also vary by scenario. The IEA’s 2026 estimates for data centre electricity emissions in 2035 range from 300 Mt of CO₂ in its Base Case to 500 Mt in its Lift-Off Case. Neither number isolates AI’s share, and neither is a certainty. The gap illustrates why a single forecast can give a misleading impression of precision. IEA: AI and climate change.
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Can AI help fight climate change?
AI can also help reduce emissions in particular applications. The IEA estimates that broad adoption of existing AI applications could yield emissions reductions equivalent to around 5% of energy-related emissions in 2035. This is a potential, not a forecast of reductions that will automatically occur. Realizing it depends on overcoming barriers to adoption, and rebound effects—where efficiency or savings lead to more use—could reduce net gains. IEA: Energy and AI, executive summary.
So AI is neither inherently climate-saving nor inevitably a climate disaster. Its net effect depends on the electricity and infrastructure it requires, the applications people actually adopt, and whether those applications deliver emissions reductions that exceed any added demand.
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What about water and other resource impacts?
Data centre impacts are not limited to electricity. Cooling can use water, and water is also used in electricity generation and chip manufacturing. These impacts vary with cooling technology, local climate and power source. The European Environment Agency’s 2025 discussion relays a Morgan Stanley projection for combined cooling and power-generation water use; that is a secondary estimate, not a directly measured, AI-only global footprint. European Environment Agency: Artificial intelligence and sustainable consumption in Europe.
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What can we conclude from the numbers?
- Data centres are a growing source of electricity demand, and AI-focused facilities are growing especially quickly.
- Most widely cited global figures cover all data centre workloads, so they cannot be used as AI-only energy or emissions totals.
- The climate impact of electricity demand depends in part on the grid supplying each facility; global averages conceal local differences.
- AI applications may cut emissions in some uses, but those potential reductions are conditional and may be offset in part by rebound effects.
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