The water footprint of artificial intelligence could reach 9.3 trillion litres annually by 2030, which would be equivalent to the domestic water requirements of approximately 1.3 billion people in Sub-Saharan Africa, a new report by the United Nations University Institute for Water, Environment and Health (UNU-INWEH) has suggested.
According to the report, entitled Environmental Cost of AI’s Energy Use: Carbon, Water and Land Footprints, by the end of the decade, data centres powering AI will collective consume around 945 terawatt-hours of electricity – nearly triple the combined annual electricity use of Pakistan, Bangladesh, and Nigeria, countries which are home to more than 650 million people.
According to the authors, public debate on the emissions impact of data centres provides only part of the picture, with water consumption and land use also major contributors to AI’s environmental footprint.
‘Technological transformation’
“This report is not a case against artificial intelligence, a technological transformation that is improving the lives of billions of people around the world,” commented Professor Kaveh Madani, director of UNU-INWEH, who led the investigation team. “It is a call for using it responsibly and addressing its unintended impacts proactively to make it sustainable and equitable.
“We have a narrow window to ensure that the backbone of the technological revolution of our era develops within planetary limits, and that the communities who provide the critical minerals for advancing AI and the ones that host its infrastructure and e-waste are also among those who benefit from it.”
As the report notes, ChatGPT processes around 2.5 billion prompts each day, with the process of generating responses to user requests accounting for between 80% and 90% of total AI energy use. This level of activity adds up to around 383 GWh of electricity per year.
In addition, data centres around the world consumed an estimated 448 TWh of electricity in 2025, which, if treated as a nation, would make them the world’s 11th largest consumer of electricity, ahead of Saudi Arabia and behind France.
Resource consumption
As the report warns, improvements in efficiency may not be enough to reduce overall resource consumption by AI – as systems become cheaper and more efficient, increased usage is likely to offset those gains.
“A lot of people think that the environmental footprint of AI reduces as technology improves and processes become more efficient. But that is only a partial picture of the overall problem,” commented Professor Madani, a co-author of the report who was recently named the 2026 Stockholm Water Prize Laureate.
“More efficient and affordable AI and energy mean more consumption of AI, making the overall footprint far bigger than what we save through efficiency gains.” Read more here.
