The Case and Model for Real-Time AI Cost Visibility at the Infrastructure Layer
TechTarget, Tuesday, August 19th, 2025
Traditional cloud FinOps breaks on AI because tokens are not taggable resources like VMs.
Gartner projects 47% growth in AI spending in 2026, but enterprises cannot control it without real-time visibility into what actually drives cost.
Conventional cloud cost management fails here because token calls are not taggable resources the way virtual machines are, and autonomous agents can burn through budget with no oversight trigger.
The author proposes moving cost attribution down from the application layer to the infrastructure layer using eBPF kernel-level sensors, which track continuously without heavy instrumentation.
That shifts governance from periodic top-down audits to real-time practitioner accountability, letting organizations treat AI as a managed investment rather than an unpredictable expense.