---
id: "action-measure-friction"
type: "action-item"
source_timestamps: ["§ The Takeaways for Managers", "¶14", "¶15"]
tags: ["analytics", "log-analysis", "user-experience"]
related: ["concept-ai-friction", "claim-self-reports-fail", "contrarian-adoption-vs-friction"]
action: "Analyze standard AI usage logs for behavioral signs of friction, such as repeated rephrasing and arguments."
outcome: "Reveals hidden coordination costs and true user struggles that adoption metrics and surveys obscure."
speakers: ["Aleksandra Przegalinska", "Tamilla Triantoro", "Leon Ciechanowski", "Konrad Sowa", "Anna Kovbasiuk", "Richard B. Freeman"]
sources: ["tail1"]
sourceVaultSlug: "hbr-seg-tail1"
originDay: 1
articleStem: "hbr-tail-113-ai-personality-problem"
sourceUrl: "https://hbr.org/2026/06/does-your-ai-have-a-personality-problem"
sourceTitle: "Does Your AI Have a Personality Problem?"
---
# Measure Friction in Usage Logs

**Action:** Analyze standard AI usage logs for behavioral signs of friction, such as repeated rephrasing and arguments.

**Outcome:** Reveals [[concept-hidden-coordination-costs|hidden coordination costs]] and true user struggles that adoption metrics and surveys obscure.

**Detail:** Stop relying solely on **adoption metrics** (log-ins, query volume) and satisfaction surveys — the latter [[claim-self-reports-fail|fail to detect friction]] and the former are a [[contrarian-adoption-vs-friction|vanity metric]]. Instead, actively mine ordinary usage logs for behavioral signals of [[concept-ai-friction|friction]]:

- Abnormally long back-and-forth exchanges
- Users repeatedly rephrasing the same prompt
- Instances of users arguing with the system

This is Step 2 of the [[framework-managerial-takeaways|three-step governance framework]].