AI Surge Accelerates the Transition to Liquid Cooling: Rethinking Energy and Water Use in Data Center Cooling

Abstract The power density of AI workloads is rapidly driving shifts to liquid cooling. This study rethinks and assesses the global impact on energy and water demand of this cooling transformation. Results suggest that liquid cooling can reduce cooling energy use by 25-56% relative to air cooling, offering substantial energy savings for GW-scale AI data centers. Best-practice PUE values could be as low as 1.07-1.08 for today’s systems and 1.03-1.04 for emerging designs and WUE values from 0.38 to 2.63 L kWh⁻¹, depending on temperature conditions. We identify global free-cooling rack inlet temperature thresholds of 33 °C for evaporative systems and 49 °C for dry systems, demonstrating the practicality of 100% free cooling in many locations. The model finds that minimum PUEs do not necessarily coincide with minimum total energy use. Results quantify the large sustainability potential of liquid cooling and provide actionable targets for data center design and policies.