Power usage effectiveness (PUE) has been the go-to metric for measuring data center efficiency for almost two decades. But in the AI era, what once was sufficient for CPU-centric environments is no longer adequate for facilities hosting GPU-based workloads operating on an entirely different scale. Power consumption must be balanced against water use, carbon emissions, compute efficiency, energy reuse, and grid interaction.

Explore the benefits and limitations of PUE and the metrics that complement it as part of a multidimensional framework that views AI infrastructure efficiency from a systems-level perspective.