---
id: "action-track-human-ai-handoffs"
type: "action-item"
source_timestamps: ["§ They Measure Real-World Performance", "¶17", "¶18"]
tags: ["metrics", "kpis", "human-ai-collaboration"]
related: ["claim-traditional-training-metrics-fail", "entity-ford-motor-company", "claim-adoption-is-continuous", "framework-building-ai-with-workers"]
action: "Replace training hours with metrics tracking the speed, accuracy, and frequency of human-AI interactions."
outcome: "Provides a true measure of workforce capability and highlights friction points in system design or workflow."
sourceUrl: "https://hbr.org/2026/05/the-best-manufacturers-build-ai-with-workers-not-for-them"
sourceTitle: "The Best Manufacturers Build AI with Workers, Not for Them"
sources: ["adoption"]
sourceVaultSlug: "hbr-seg-adoption"
originDay: 9
articleStem: "hbr-cl-78-build-ai-with-workers"
---
# Track Human-AI Handoff Metrics

**Action:** Abandon participation-based training metrics (courses completed, hours logged). Instead, instrument workflows to track operational signals of human-AI collaboration. Specifically measure:

- the **speed and accuracy of human-AI handoffs**;
- the **time taken to resolve exceptions**;
- **how frequently operators validate or correct** the system's recommendations.

**Expected outcome:** a true measure of workforce capability and a spotlight on friction points in system design or workflow.

This operationalizes Pillar 3 of the [[framework-building-ai-with-workers]], directly answers [[claim-traditional-training-metrics-fail]], feeds the continuous view in [[claim-adoption-is-continuous]], and is exemplified by [[entity-ford-motor-company]]. **Guardrail (enrichment):** pair these operational metrics with periodic qualitative review — a narrow KPI set can under-measure judgment, safety, and learning transfer, and can invite gaming.


## Related across articles
- [[action-measure-trust-factors]]