Behind millions of dollars of funding in AI sit enterprises with just a 5% average utilisation rate. Inference cost plus cost of ownership also rose to 41% from 34%

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ai-infrastructure gpu-utilization inference-costs enterprise-ai cost-optimization hardware-allocation

Summary

Enterprises that rushed to buy massive GPU fleets for AI now face low utilization rates (5%) and rising costs (inference cost plus cost of ownership rose to 41% from 34%), highlighting significant infrastructure inefficiencies in AI deployment.

Well, Over the last few years after the Chat GPT rolled out, companies rushed to buy massive GPU fleets because AI demand exploded and compute was scarce but i think now it depends on more than just utilization like utilization, scheduling, inference efficiency, routing, governance, energy access, and operational management. The irony hits perfect, the technology designed to have the most efficient impact on human lives has this huge inefficiency of infrastructure problem Where majority budget goes out in figuring out allocation of hardware Source: [https://winbuzzer.com/2026/05/11/enterprises-face-underused-gpu-fleets-as-ai-costs-rise-xcxwbn](https://winbuzzer.com/2026/05/11/enterprises-face-underused-gpu-fleets-as-ai-costs-rise-xcxwbn)
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