Is AI really using up our drinking water?

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1. 1

   Data centre water consumption

   npj Clean Water (Mytton)Published Feb 15, 2021Checked Oct 9, 2026

   “To reliably support the online services used by these billions of users, data centres have been built around the world to provide the millions of servers they contain with access to power, cooling and internet connectivity. Whilst the energy consumption of these facilities regularly receives mainstream and academic coverage, analysis of their water consumption is scarce. Data centres consume water directly for cooling, in some cases 57% sourced from potable water, and indirectly through the water requirements of non-renewable electricity generation. Although in the USA, data centre water consumption (1.7 billion litres/day) is small compared to total water consumption (1218 billion litres/day), there are issues of transparency with less than a third of data centre operators measuring water consumption. This paper examines the water consumption of data centres, the measurement of that consumption, highlights the lack of data available to assess water efficiency, and discusses and where the industry is going in attempts to reduce future consumption.”

2. 2

   The carbon and water footprints of data centers and what this could mean for artificial intelligence.

   Patterns (New York, N.Y.) (de)Published Dec 17, 2025Checked Oct 9, 2026

   “Although there are ways to estimate the global power demand of artificial intelligence (AI) systems, it remains challenging to quantify the associated carbon and water footprints. The lack of distinction between AI and non-AI workloads in the environmental reports of data center operators makes it possible to assess the environmental impact of AI workloads only by approximating them through data centers' general performance metrics. The environmental disclosure of tech companies is, however, often insufficient to determine even the total data center performance of these companies. The shortcomings in the environmental disclosure of data center operators could be remedied with new policies mandating the disclosure of additional metrics. Because the environmental impact of data centers is growing rapidly, the urgency of transparency in the tech sector is also increasing. The carbon footprint of AI systems alone could be between 32.6 and 79.7 million tons of CO2 emissions in 2025, while the water footprint could reach 312.5-764.6 billion L.”

3. 3

   The water footprint of artificial intelligence: Emerging solutions and governance imperatives.

   Water research (Barnett-Itzhaki)Published Apr 2, 2026Checked Oct 9, 2026

   “Artificial intelligence (AI) is increasingly run on high-density computing infrastructure, yet its environmental footprint is still assessed mainly through electricity use and associated greenhouse-gas emissions. A critical, less visible dimension is water: AI infrastructure consumes freshwater through evaporative cooling, indirect water use in electricity generation, and water-intensive semiconductor manufacturing. Projections suggest AI's global water footprint could reach 4.2-6.6 billion cubic meters annually by 2027. Many data centers are located in water-stressed regions. While technologies, including cold-climate siting, natural water body cooling, waterless designs, and waste heat recovery, can reduce on-site demand, their deployment remains limited. This work introduces "digital water sobriety" as a governance framework linking evaluation of which AI applications justify freshwater consumption, water conscious siting, and mandatory facility-level water use transparency. Achieving water-sustainable AI demands not merely technological optimization but fundamental policy reform integrating water constraints into computational infrastructure planning.”

4. 4

   Data Centers Water Footprint: The Need for More Transparency

   AGU Advances (Privette et al.)Published Feb 27, 2026Checked Oct 9, 2026

   “The exponential growth of artificial intelligence (AI) has driven the rapid global expansion of data centers, raising serious concerns about their environmental impact—particularly water use. While national and global water consumption by data centers may seem modest compared to other users, their localized impacts can be significant—especially in regions already facing water stress or drought. This commentary examines the multi‐faceted water footprint of data centers, encompassing direct cooling, electricity generation, and supply chain water demands. It highlights major gaps in transparency around how much water data centers use, which undermine effective regulation, innovation, and community planning. To ensure the sustainable growth of digital infrastructure and the preservation of water resources, comprehensive monitoring and public disclosure of water use are essential. Equally important are resilient water infrastructure planning and stronger collaboration between industry and communities.”

5. 5

   Assessing environmental impacts of rapid data centre expansion on energy consumption, water resources, and emissions

   International Journal of Research in Engineering (Daramola)Published Jan 1, 2023Checked Oct 9, 2026

   “The methodology combines installed computing capacity, server utilisation, Power Usage Effectiveness (PUE), grid carbon intensity, Water Usage Effectiveness (WUE), cooling-system requirements, electricity-generation mix, and operational growth rates to estimate direct and indirect environmental burdens. Energy consumption is decomposed into computing and non-computing loads, while water accounting distinguishes on-site cooling demand from electricity-related water consumption. Scope 1 and Scope 2 emissions are evaluated alongside location-dependent grid characteristics to identify geographic disparities in environmental exposure. Scenario and sensitivity analyses test renewable-energy penetration, cooling efficiency, workload growth, utilisation, and water-stress conditions. The resulting framework identifies environmental thresholds at which capacity expansion intensifies resource constraints, providing evidence for sustainable siting, infrastructure planning, technology selection, and regulatory decision-making.”

6. 6

   AI Uses How Much Water? Navigating Regulation of AI Data Centers' Water Footprint Post-Watershed Loper Bright Decision Comments

   ThinkTech (Texas Tech University) (Garcia)Published Jan 1, 2025Checked Oct 9, 2026

   “AI Uses How Much Water? Navigating Regulation of AI Data Centers’ Water Footprint Post-Loper Bright Decision examines the growing water demands of artificial intelligence data centers and the regulatory challenges they present. It explains how the Supreme Court’s "Loper Bright" decision reshapes administrative deference and affects agency authority over water-use regulation. The discussion situates AI data centers within existing federal and state water management frameworks, highlighting gaps exposed by evolving judicial standards. It also considers the implications for environmental oversight when agencies must justify water-related regulations without broad judicial deference. The abstract concludes by identifying emerging regulatory pathways for addressing the water footprint of AI infrastructure in a post-"Loper Bright" landscape.”