Myth check: “AI is destroying the environment”
AI-focused data centres used about 0.5% of the world's electricity in 2025. That is small but growing fast, and local strain is real.
The claim in full “AI is destroying the environment.”
Energy: AI requests vs everyday things
Watt-hours. Log scale: each gridline is 10× the previous. Blue = AI.
What this measures: How much electricity different AI requests use, next to everyday activities.
AI figures are company disclosures (Google, OpenAI) or published models (Microsoft-led Joule study, Epoch AI, IEA); none is independently audited. Household figures assume typical UK appliances (Hannah Ritchie). The web-search figure is Google's from 2009.
Show data table and sources
| Item | Value | Note |
|---|---|---|
| One AI text prompt (Gemini median) | 0.24 Wh | Google, all overheads |
| One Google web search (2009 figure) | 0.3 Wh | old figure |
| Average ChatGPT query | 0.34 Wh | OpenAI, method unstated |
| Long reasoning-style AI query | 3.91 Wh | modelled median |
| LED bulb for 1 hour | 10 Wh | |
| Microwave for 1 minute | 16.7 Wh | |
| Charging a smartphone | 19.4 Wh | |
| Laptop for 1 hour | 20 Wh | |
| AI query over a 100,000-token document | 40 Wh | estimate, paid once per upload |
| Agentic AI task with reasoning | 50 Wh | IEA, GPU-only |
| TV for 1 hour | 60 Wh | |
| Streaming video for 1 hour | 77 Wh | 2019, incl. device |
| Boiling a full kettle | 100 Wh |
- How much energy does Google's AI use? We did the math (Google Cloud)
- The Gentle Singularity (Sam Altman)
- Energy Use of AI Inference, Efficiency Pathways, and Test-Time Scaling (Microsoft et al. (Joule))
- How much energy does ChatGPT use? (Epoch AI)
- Key Questions on Energy and AI (IEA)
- Energy use comparisons (Hannah Ritchie)
- Greenhouse gas equivalencies calculator: calculations and references (US EPA)
- Factcheck: What is the carbon footprint of streaming video on Netflix? (Carbon Brief)
- Green-minded Google gets red-faced over search energy consumption claims (quotes Google's 2009 figure) (eWeek)
What the data shows
The worry: AI runs on huge data centres that burn electricity and use up water, and the boom is making climate change and local pollution worse.
What’s true. The growth and the local effects are real. Electricity use by AI-focused data centres grew about 50% in 2025, and the IEA projects it will more than triple by 2030. Where data centres cluster, they are 20–30% of electricity demand (over a quarter in Virginia, over 20% in Ireland). LBNL projects US data centres could reach 11.8% of US electricity by 2030. In Memphis, xAI ran gas turbines while its permits were disputed, in an area already failing federal air-quality standards. Bloomberg found most new US data centres since 2022 are in water-stressed areas.
What the data shows worldwide. All data centres used about 1.5% of the world’s electricity in 2025, and AI-focused ones about 0.5% (about 155 TWh). The IEA projects data-centre emissions of about 350 Mt CO₂ by 2035, roughly 2% of emissions from electricity. Energy per text prompt is also falling fast: Google reports a 33× drop in one year.
What it means
AI is not a large part of the world’s emissions or water use today. The real harm is local: a big data centre can strain a town’s power grid, air or water. The fair position is to watch the growth and judge each site where it is built, rather than call AI either harmless or a global disaster.
Caveats
- “The environment” bundles carbon, water, air quality, land and supply chains. The evidence is strongest for local strain and weakest for global-scale harm today.
- Projections are uncertain in both directions.