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A UN report warns AI’s environmental impact goes beyond carbon, highlighting massive water use by data centres. A single text prompt can consume about 29 ml of water, while training models like GPT-4 used around 600 million litres. By 2030, global data centre water use could reach 9.3 trillion litres, raising sustainability concerns.

The cost of water due to AI usage is a reason for concern across the globe. That question you typed into ChatGPT this morning? It cost roughly two tablespoons of water. Multiply that by 2.5 billion daily prompts, and the numbers start to look very different.

A landmark new report from the United Nations University Institute for Water, Environment and Health (UNU-INWEH) has put hard figures on what was previously only vaguely understoodv- the full environmental toll of the world's surging appetite for artificial intelligence. The findings go well beyond carbon emissions, and they paint a far more complicated picture of what it means to build a green AI future.

The UNU-INWEH report quantifies AI's carbon, water, and land footprints together for the first time. Its headline projection is stark - by 2030, data centres powering AI are expected to consume 945 terawatt-hours of electricity annually, nearly triple the combined electricity use of Pakistan, Bangladesh, and Nigeria, three countries with a combined population of over 650 million.

The water consequences of that energy demand are equally striking. The report projects that by 2030, the water footprint of global data centres will reach 9.3 trillion litres, an amount sufficient to meet the basic annual domestic water needs of every person in Sub-Saharan Africa, all 1.3 billion of them.