For data centers pressured by the demands of AI, liquid cooling has moved from a specialty option to a baseline requirement for today’s most power-dense data facilities. Driving the transition is a mismatch between heat levels from AI training clusters that legacy air cooling can hardly handle, and data center operators who now face sustainability concerns about carbon emissions and water consumption.
Liquid coolant carries heat far more effectively than air and can be delivered closer to the hottest components. That matters as GPUs and accelerators concentrate more watts into smaller footprints. The practical result is higher rack density, lower reliance on server fans, and a clearer path to deploying next-generation hardware without sprawling a facility’s footprint.
But the current state of the market is less about a single liquid cooling solution and more about a mix of approaches, with each having its trade-offs in cost, complexity, and retrofit feasibility.
Complexities of Liquid Cooling
The most common near-term solution is direct-to-chip cooling using cold plates. In this design, a closed loop routes coolant through a plate attached to the processor package, extracting heat at the source. Operators like the approach because it fits existing server form factors and avoids the operational leap that immersion cooling can represent.
Microsoft has conducted a life cycle assessment, published in Nature, that looks beyond day-to-day operations and examines cooling technologies from cradle to grave, including the impacts tied to manufacturing, transport, and eventual disposal. In this analysis, cold plates and immersion approaches reduce lifecycle greenhouse gas emissions and energy demand compared with air cooling, and can substantially reduce water consumption as well.
The study also notes that the nature of the power grid still influences carbon outcomes: even the best cooling choice cannot make up for an emissions-heavy electricity mix.
Water use is emerging as a major concern in the liquid cooling debate. Liquid cooling of course means more water, but the real level depends on the facility’s broader thermal design. Many air-cooled data centers rely on evaporative cooling, which can consume significant water in operation. In contrast, modern liquid systems are often closed-loop and can limit make-up water needs to periodic quality management.
The key point here is how heat is ultimately rejected. Is it by dry coolers, chillers, evaporative systems, or heat reuse? The mix of these solutions at a data center, with their positives and negatives, adds up to a given data center’s heat management profile.
Heat Reuse, Colos in the Mix
Heat reuse is one of the more consequential second-order benefits starting to show up in hyperscaler roadmaps. If heat is captured in a controllable liquid loop, it becomes easier to redirect for building heating or other industrial applications. Google, for instance, has leaned into heat reuse partnerships as it expands liquid and immersion cooling in support of AI infrastructure. The data center industry is treating heat as something to manage today and monetize tomorrow, even if most projects remain site-specific.
Colocation providers are also repositioning around liquid capability. High-density AI-ready offerings increasingly advertise rack support in the 100+ kW range, with some operators targeting 150 kW per rack in specialized deployments. That headline number often assumes direct liquid cooling, rear-door heat exchangers, or hybrid designs that split the thermal load between liquid at the rack and traditional air handling for the room.
Will Liquid Cooling Solve the Growing Thermal Problem?
While liquid cooling is clearly a growing trend in data centers, the harder question is whether it will be enough to handle growing heat levels. The answer seems to be yes, but with limitations.
Liquids can address the immediate thermal limits that would otherwise cap AI deployment. But cooling is only one element in the new data center equation. Power availability, grid interconnection timelines, and sustainability goals are all increasing the pressure on data facilities. Liquid cooling can improve efficiency and, in some designs, reduce water use, but it does not reduce the electricity consumed by the compute itself.
And liquid cooling has its own issues. When the cooling loop runs to the chip, failures can cascade quickly. Maintenance discipline becomes mission-critical. Concerns around filtration, corrosion control, leak detection, and fluid quality management move from best practice to true necessity. The industry’s shift to liquid is not just a facilities upgrade, it’s a major infrastructure change, and that’s never easy.
