Cheaper tokens, bigger bills: The new math of AI infrastructure

As enterprise AI moves from training to production inference, infrastructure is becoming the main cost center.

Agentic workloads create continuous, unpredictable traffic, driving up demand for GPUs, storage, and networking.

Even as cost per token falls, overall usage is rising faster, pushing total AI spend higher.

Leaders are focusing on cost per token and GPU utilization, while favoring full-stack platforms to cut inefficiencies.