Artificial intelligence could consume enough water to meet the basic annual needs of 1.3 billion people and use more electricity than over 650 million people by 2030, according to a new report by the United Nations University Institute for Water, Environment and Health (UNU-INWEH).
The report projects that AI-driven data centers will consume 945 terawatt-hours (TWh) of electricity annually by the end of the decade, nearly three times the combined electricity consumption of Pakistan, Bangladesh and Nigeria.
The report said AI’s growing environmental impact extends beyond carbon emissions. The expansion of data centers will also significantly increase water consumption for cooling and power generation.
According to the report, the land footprint of AI’s electricity demand could exceed 14,500 square kilometers by 2030, roughly twice the size of Indonesia’s Jakarta metropolitan area.
UN researchers warned that assessing AI’s sustainability solely through carbon emissions overlooks its broader environmental impact, as cleaner energy sources can still require substantially more water and land.
The study also found that AI inference—the process of running AI models to answer user requests—now accounts for 80 to 90 percent of AI’s total electricity use, far exceeding the energy required to train the models.
ChatGPT alone is estimated to process about 2.5 billion prompts every day, consuming roughly 383 gigawatt-hours (GWh) of electricity annually.
The report said more demanding AI tasks, particularly image and video generation, consume significantly more energy than basic text-based applications. Generating a single AI image can require around 1,450 times the energy of a basic text-classification task, while producing a short AI-generated video can consume as much electricity as processing 200,000 spam-detection requests.
The report concluded that governments and technology companies should evaluate AI’s environmental impact using carbon, water and land footprints together, rather than relying on emissions alone, as global investment in AI infrastructure continues to accelerate.
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