Artificial intelligence cost observability records resource use with enough context to explain it. Instead of a provider total, it can attribute model calls and related costs to a run, user segment, workflow, subagent and policy intervention.
This visibility helps teams find expensive loops, expanding context and inefficient tools. Cost data should be connected to completion and quality because reduced spending is not useful if the workflow fails more often.
