Autonomy Audit for Ticket Triage (QA)

Autonomy Audit for Ticket Triage (QA)

1. 01

   Map every ticket type to a triage action and an owner

   List the categories your client's support queue actually receives, then assign each to auto-resolve, agent-assisted, or escalate-to-human. This baseline prevents the triage layer from guessing on edge cases.

2. 02

   Measure current deflection and resolution rates before tuning

   Record the percentage of tickets auto-resolved and average first-response time over a 30-day window. These numbers become the benchmark for judging whether the automation is helping or just adding noise.

3. 03

   Review the last 50 escalated tickets for misrouting patterns

   Check whether the triage logic sent emotionally charged or complex cases to the right queue. A single angry customer routed to a billing bot can cost more than the automation saves.

4. 04

   Test the fallback path when confidence scores are low

   Confirm that tickets below the confidence threshold route to a human with full context, not to a dead-end auto-reply. The goal is graceful degradation, not silent failure.

5. 05

   Verify that sensitive data stays inside the client's approved boundary

   Audit which fields the triage model reads and whether any PII or contract data passes through a third-party API. Self-hosted or on-prem options may be required for regulated clients.

6. 06

   Document the human oversight cadence and escalation SLA

   Write down who reviews auto-resolved tickets daily, how often the model's decisions are sampled, and the maximum time a critical issue can sit in a queue. This turns the tool into a managed service, not a black box.

7. 07

   Run a shadow-mode comparison for one week before full rollout

   Let the triage logic run in parallel with your existing process, comparing its routing decisions against what a human would do. This surfaces gaps without risking live customer experience.