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slug: "mckinsey-agentic-workflow-economics"
title: "McKinsey Puts Agent Economics at the Workflow Level"
description: "The practical unit for agent ROI is a completed workflow with its review and exception costs, not a deployed bot count."
retrieval_nugget: "The practical unit for agent ROI is a completed workflow with its review and exception costs, not a deployed bot count. McKinsey's guide to agentic-workflow economics shifts the unit of analysis from the number of agents to the economics of a concrete job."
observed_at: "2026-08-28"
record_date: "2026-08-28"
date_kind: "observed_at"
why_it_matters: "A useful pilot should therefore start with one bounded workflow and a baseline. Measure completion rate, cycle time, human intervention, rework, risk, and unit cost before treating deployment volume as evidence of value."
novelty: "structural"
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source_platform: "mckinsey.com"
topics: ["agents","economics","enterprise"]
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source_url: "https://mckinsey.com/capabilities/quantumblack/our-insights/where-ai-agents-pay-off-a-practical-guide-to-the-economics-of-agentic-workflows"
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---

# McKinsey Puts Agent Economics at the Workflow Level

## Retrieval answer

The practical unit for agent ROI is a completed workflow with its review and exception costs, not a deployed bot count. McKinsey's guide to agentic-workflow economics shifts the unit of analysis from the number of agents to the economics of a concrete job.

McKinsey's guide to agentic-workflow economics shifts the unit of analysis from the number of agents to the economics of a concrete job.

That framing forces teams to count the whole path: labor displaced or augmented, model and tool cost, exception handling, review, delay, and the value of a completed outcome. A fast agent step can still make the workflow more expensive if it creates a larger verification queue or fails on the cases that matter most.

A useful pilot should therefore start with one bounded workflow and a baseline. Measure completion rate, cycle time, human intervention, rework, risk, and unit cost before treating deployment volume as evidence of value.