Short answer
AI datacenters use water primarily for cooling systems. Modern GPUs produce large amounts of heat, and many facilities rely on evaporative cooling or chilled water systems to keep servers operational.
Cooling systems require water
AI servers operate continuously and generate significant heat during inference and training workloads. Water is often used because it is highly effective at transferring and dissipating heat.
Modern AI hardware generates enormous heat
Large GPU clusters can consume megawatts of electricity. Most of that electrical energy eventually becomes heat, which must be removed to avoid damaging equipment and reducing performance.
Location matters
Water usage varies depending on climate, cooling technology, and datacenter design. Facilities located in hot or dry regions may face greater cooling challenges and higher water demand.
AI growth could increase water demand
As AI adoption grows worldwide, more datacenters and larger GPU clusters may increase electricity and water consumption. Many companies are now exploring alternative cooling technologies and efficiency improvements.