Request use-case-specific evidence linking triage errors: Which evidence best resolves that uncertainty?
Use-case-specific evidence linking triage errors to customer impacts tests the relevant harm metric directly.
The question
A travel company plans to use AI for customer-support triage. Intended use, users, data access, owners, monitoring, and escalation controls are defined, but the approval team must determine whether the supplier’s service metric reflects customer harm. Which evidence best resolves that uncertainty?
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- Require a broader dashboard combining uptime, latency, accuracy, complaints, and escalation data.A broad dashboard may be useful, but without defined links to customer impacts it may still leave the specific uncertainty unresolved.
- Compare the supplier’s uptime metric with its support-volume trend.Uptime and volume provide context, yet they do not directly measure whether triage errors harm affected customers.
- Review the supplier’s response-time service report.Response time measures operational speed, but it may not reveal misrouting, denial, or other customer-impacting outcomes.
- Request use-case-specific evidence linking triage errors to customer impacts. ✓This evidence directly connects system outcomes with customer effects, testing whether service performance reflects the relevant harm.
The trap
Ask whether the metric measures what can affect people, rather than merely how quickly or reliably the service runs. How to remember it
Use-case-specific evidence linking triage errors to customer impacts tests the relevant harm metric directly.
How many of these would you get right?
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