A new UN University report warns that AI data centers will consume 9.3 trillion liters of water by 2030, equal to the basic water needs of 1.3 billion people in Sub-Saharan Africa. The report says current environmental assessments focus too narrowly on carbon emissions from training AI models, while ignoring the much larger water and land footprint from cooling and powering data centers. The report highlights that inference costs, the energy used to run AI models and answer prompts, make up 80 to 90 percent of total AI energy use. Running ChatGPT alone uses an estimated 383 GWh per day. By 2030, data centers powering AI will use 945 terawatt-hours of electricity, triple the combined electricity use of Pakistan, Bangladesh, and Nigeria. The authors warn that switching to renewables like bioenergy could cut carbon emissions by 70 percent but increase water footprint by 30 times and land footprint by 100 times. They caution that making AI more efficient may paradoxically increase overall environmental impact by driving more consumption.
