Liquid-cooled AI systems expose storage architecture limitations — impact on data center efficiency.

Context

Liquid-cooled AI systems are rewriting the rules of data center infrastructure, but most deployments have not fully transitioned to liquid cooling for storage. This hybrid approach creates an operationally inefficient situation, where organizations absorb the cost premium without capturing the full total cost of ownership benefit. Relevant for infrastructure leaders evaluating storage solutions for AI workloads.