The AI compute gap: Enterprises are buying infrastructure faster than they can measure what it costs

Enterprises are rapidly increasing AI infrastructure spending but struggle to measure its true costs. Most rely on hyperscalers and model-provider APIs, yet plan to evaluate specialized AI clouds and alternative accelerators soon. GPU utilization is low, and fewer than half rigorously track compute costs, creating a significant visibility gap in AI economics.

Enterprises risk inefficient spending and poor cost control without better measurement of AI infrastructure economics.

Teams tracking Core AI, Infrastructure, product strategy, operations, and market positioning.

Enterprises should improve tracking and analysis of AI compute costs before expanding infrastructure.