AI Demand Could Consume 1.7 Trillion Gallons of Water a Year by 2027
Updated
Updated · ECOticias · Jun 11
AI Demand Could Consume 1.7 Trillion Gallons of Water a Year by 2027
3 articles · Updated · ECOticias · Jun 11
Summary
1.1 trillion to 1.7 trillion gallons of annual water withdrawal could be tied to global AI demand by 2027, researchers estimated, putting the hidden resource cost of chatbots, search tools and image generators into sharper focus.
17.6 fluid ounces of water may be used for a 100-word ChatGPT email when counting both server cooling and electricity generation, though the total varies by data center design, local climate, grid mix and response length.
Google said Alphabet used 8.1 billion gallons of water in 2024—7.8 billion at data centers—with total consumption up 28% from 2023; Microsoft reported about 1.5 billion gallons in FY24, 42% from high-stress areas.
U.S. data centers directly consumed about 17.4 billion gallons in 2023, while their electricity use carried an indirect water footprint of roughly 211 billion gallons, underscoring that power demand drives much of AI's water burden.
Chile's scrutiny of Google's $200 million data-center plan during drought highlights why researchers want facility-level disclosure and wider use of air cooling, recycled water and smarter siting in water-stressed regions.
Could 'green' energy for AI actually be worsening the global water crisis?
Who will win the battle for water: Big Tech or local communities?
The Hidden Thirst of AI: Data Centers, Water Scarcity, and the Urgent Need for Sustainable Solutions
Overview
The rapid growth of Artificial Intelligence is driving a sharp rise in water demand, mainly because data centers need large amounts of water to keep their servers cool. This makes water a critical resource for ongoing operations and is forcing regions—especially those already facing scarcity—to rethink how they plan and manage water. As AI infrastructure expands, its water use is becoming a major factor in environmental discussions, highlighting the need to include AI in broader water resource planning. The scale of this demand shows that AI’s impact on water is both immediate and significant, requiring urgent attention from policymakers and industry leaders.