Four water insecurity concerns about datacenters driving the AI revolution

Datacenters are powering the Artificial Intelligence (AI) revolution. However, their water insecurity risks remain neglected. Limited research on the matter quantifies water demand at national or watershed-scales and estimates water use associated with training and using AI models. Research fails to examine water insecurity concerns held by households and communities where datacenters are planned or are operational. This article identifies four water insecurity concerns in the U.S. by synthesizing public reporting and legal filings involving non-governmental organizations, citizen coalition groups, investigative reporters, and individual citizens. These concerns include how datacenters’ development and operation can (i) undermine the democratization of water governance; (ii) contribute to unsustainable water use and rising utility costs; (iii) reduce the flexibility and resilience of water use decision-making; and (iv) increase water use across scales as a result of rising electricity demand. Three areas for future research are identified from the cases reviewed. First, local governments and utilities do not always readily provide water use data associated with datacenter operations; hence, public records should be requested and shared to democratize decision-making. Second, water-related risks posed to public health, rural and land-based livelihoods, and ecosystems from datacenter operations require context-specific empirical investigation. Third, examining whether and how specific water governance arrangements can engender acute health, economic, and environmental risks, especially under extreme events such as heatwaves or droughts, requires institutional analyses. Overall, analyzing datacenters’ volumetric water use within local contexts offers a more relevant analysis of water insecurity concerns and experiences.