# Benchmarking Agent Economics: What Normal Costs Look Like by Vertical

Published 2026-08-11 · Brian Diamond

Track: finops

Segment: strategy

There is no universal “right” agent cost. Verticals differ in outcome definition, human baseline, and risk tolerance. Benchmarking agent economics means comparing like outcomes inside a peer set — then explaining variance with attribution data.

## Build an honest benchmark

Normalize on outcome, include tool and retry spend, and separate pilot from production. Publish internal benchmarks before chasing external vanity numbers.

Use [cost per outcome](https://www.onaro.io/blog/how-to-calculate-cost-per-outcome-for-ai-agents) and the [2026 AI Agent Economics Report](https://www.onaro.io/resources/2026-ai-economics-report).

Onaro Meridian is [FinOps for agentic AI](https://www.onaro.io/finops-for-agentic-ai): the system of record that attributes, controls and books what AI agents spend.

Canonical: https://www.onaro.io/blog/benchmarking-agent-economics-by-vertical