AI to double data centre power and water consumption by 2030, UN researchers say

The United Nations University Institute for Water, Environment and Health warns that data centre power and water consumption will double by 2030 due to AI demand, straining global resources and increasing CO2 emissions. AI currently accounts for 20% of data centre electricity use and 40% is projected by 2030, alongside rising land use and e-waste concerns, according to a June 2026 report.
Data centres are projected to consume twice as much electricity and water by 2030 as AI demand surges, according to a report by the United Nations University Institute for Water, Environment and Health released June 3, 2026. Last year, data centres globally used 448 terawatt-hours of electricity—more than Saudi Arabia’s total—with AI responsible for one-fifth of that usage. Water consumption reached 4.5 trillion litres, enough for over 600 million people in Sub-Saharan Africa, while generating 189 million tons of CO2. By 2030, power demand is expected to double to 945 TWh, equivalent to Japan’s annual consumption, with AI driving 40% of the increase. Water use will rise to 9.3 trillion litres, and CO2 emissions could hit 399 million tons. The land footprint for data centres may expand from 6,900 square kilometers in 2025 to over 14,500 square kilometers, exacerbating resource scarcity in some regions. The report highlights that AI’s physical infrastructure—including data centres, cooling systems, and mining for chips—often goes unaddressed in public discussions. Kaveh Madani, director of the institute and lead author, emphasized that unchecked expansion risks colliding with local water and power constraints. While AI could optimize energy use, overall demand is likely to grow as corporations and governments prioritize rapid scaling over sustainability. Madani warned that poorly planned data centre growth could create regional shortages, even if global resources remain available. He stressed the need for responsible planning to avoid locking in unsustainable infrastructure. The report underscores the urgency of balancing AI’s benefits with environmental costs before critical dependencies become irreversible.
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