AI Auto-Resolve Implementation Checklist

Use this AI auto-resolve implementation checklist to move from a promising demo to a controlled support workflow. The goal is not maximum automation on launch day. The goal is one narrow intent that resolves reliably and hands every uncertain case to the right person.

Phase 1: define the scope

• Choose one repeated, low-risk customer question.
• Define exactly what counts as that intent.
• List similar questions that must not qualify.
• Name the channel or queue included in the pilot.
• Assign a support owner and a technical owner.
• Document how to disable the workflow quickly.

A useful first intent has enough volume to measure, but it does not involve refunds, security, privacy, legal interpretation, account changes, or contract exceptions.

Review the AI auto-resolve examples if you need a shortlist.

Phase 2: prepare the source

• One approved article fully answers the intent.
• The direct answer appears near the top.
• Preconditions, plan limits, roles, and exceptions are explicit.
• Steps match the current product or policy.
• The source states when to contact a human.
• An owner and last-reviewed date are recorded.
• Duplicate or obsolete versions are removed from retrieval.

Run the complete knowledge base audit for AI auto-resolve before enabling customer-facing replies.

Phase 3: configure eligibility and escalation

• Allowlist the exact intent.
• Require a matching approved source.
• Set a minimum confidence or verification condition.
• Escalate angry, sensitive, ambiguous, VIP, and repeated-contact cases.
• Escalate when required customer context is missing.
• Escalate when the answer needs an exception or account action.
• Route each escalation reason to a named queue.
• Preserve the source attempt and stop reason for the agent.

Skipping is a valid result. The workflow should never generate around a missing source.

Phase 4: build a test set

Create a repeatable evaluation before using live traffic.

Test group	Minimum examples	Expected result
Clear eligible questions	10	Correct source and complete answer
Wording variations	10	Same eligible intent
Near-match questions	5	Different source or escalation
Sensitive variants	5	Immediate escalation
Missing-context questions	5	Ask safely or escalate
Follow-up and reopen cases	5	Preserve history and ownership

• A support lead reviews every expected answer.
• Sources appear in the response or internal audit record.
• The answer does not introduce unsupported details.
• The tone matches the team’s support style.
• Every failure produces a complete handoff.

Phase 5: run in draft mode

• Retrieve and draft without sending automatically.
• Record whether agents accept, edit, or reject each draft.
• Group edits by source problem, tone problem, or missing context.
• Fix source content before changing prompts to hide a content gap.
• Confirm the queue, owner, and priority stay correct.

Draft mode shows how the workflow behaves on real customer language while a human still controls the reply.

Phase 6: launch a narrow pilot

• Limit the pilot to the chosen intent and channel.
• Start with a small traffic share if the product supports it.
• Review every automated outcome during the first pilot window.
• Keep customer reply and reopen paths visible.
• Pause immediately if the source, product, or policy changes.

Protodesk’s product-specific setup is documented in the AI auto-resolve guide.

Phase 7: measure quality

Record counts rather than one vague automation percentage:

• Total incoming tickets.
• Tickets eligible for the pilot.
• Automation attempts.
• Verified resolutions.
• Skips and escalation reasons.
• Reopened or repeated contacts.
• Customer satisfaction.
• Missing or stale source incidents.

Calculate verified resolution rate against eligible tickets, then inspect reopen rate. A resolved status is not enough if the customer returns with the same issue.

Phase 8: estimate operating cost

• Estimate monthly eligible ticket volume.
• Include triage and sidekick usage around auto-resolve.
• Check whether the recommended plan covers normal and peak months.
• Set a review point before usage or top-ups surprise the team.

In Protodesk, AI triage and sidekick use one credit per action, while auto-resolve uses two credits per attempt. Use the AI credits calculator to model the mix.

Phase 9: expand carefully

Add another intent only when:

• The current source remains complete and owned.
• Reopen and escalation results are understood.
• No sensitive near-match is resolving incorrectly.
• Agents trust the handoff context.
• The team can maintain the added source.

Repeat the checklist for each intent. Do not convert a successful narrow pilot into a broad “answer everything” permission.

For the operating principles behind these controls, read safe customer support automation and the glossary guide to automated ticket resolution.