10 AI Auto-Resolve Examples for Customer Support

Good AI auto-resolve examples have three things in common: the customer asks a narrow question, an approved source contains the complete answer, and a wrong answer would not create a serious customer or business risk.

The examples below are workflow patterns, not claims about a particular company. Each one shows what the system may answer and the condition that should send the ticket to a person.

AI auto-resolve examples at a glance

Customer question	Required source	Resolve automatically when	Escalate when
“How long is the trial?”	Current pricing or trial article	The plan and trial terms are explicit	The customer asks for an exception
“How do I reset my password?”	Tested reset instructions	The account uses the documented login flow	The customer reports lockout, compromise, or missing email
“Where can I download an invoice?”	Billing how-to article	The steps are the same for every account	The invoice is wrong or payment failed
“Does this plan include feature X?”	Current plan comparison	The feature and plan are named directly	The account has a custom contract
“How do I invite a teammate?”	Product setup guide	The permission requirements are documented	The user lacks the required role
“What are your support hours?”	Public support policy	Hours and time zone are current	The question concerns an active incident
“When will my order arrive?”	Shipping policy or trusted order data	The answer can be grounded in policy or a verified status	The shipment is lost, late, or disputed
“Can I return this item?”	Current return policy	The request clearly falls inside the published window	The item is damaged, restricted, or outside policy
“How do I connect WhatsApp?”	Channel setup documentation	The workspace meets the documented prerequisites	Verification fails or an account-specific error appears
“How do I fix this known error?”	Tested troubleshooting article	The error code and environment match the article	The steps fail or the symptoms differ

1. Trial and plan-limit questions

Pricing questions are good candidates only when the public source is precise. The answer should name the plan, limit, billing condition, and date-sensitive qualification without inventing an exception.

Escalate custom discounts, nonprofit pricing, contracts, refunds, and any request to override a limit. Those require judgment or account access.

2. Password reset instructions

A reset workflow can link the official steps and explain what email to expect. It should not ask for a password, recovery code, or other secret.

Security language changes the risk immediately. “I cannot find the reset email” may need troubleshooting; “someone changed my password” should go to a human-owned security path.

3. Invoice downloads

The AI can explain where invoices live and what role can access them. That is different from interpreting a tax charge, correcting an invoice, or investigating a failed payment.

The first is documentation. The others are billing cases.

4. Feature availability

This works when a maintained plan matrix states exactly whether a feature is included. The answer should cite or link that matrix so the customer can verify it.

If the customer has a legacy plan or negotiated agreement, skip automation because the public plan page may not describe their entitlement.

5. Teammate invitations

Invitation steps are usually repeatable and low risk. A good article explains the required role, where the control appears, and what to do when an invitation expires.

Permission changes, ownership transfer, and unexpected access should escalate.

6. Support hours and response expectations

An approved service article can answer office hours, supported languages, and normal response windows. Avoid turning a general response window into a promise for an active outage or contractual SLA.

7. Shipping status explanations

There are two safe versions: explain the published shipping window, or present status from a verified order system. Do not guess from the customer’s message.

Lost packages, chargebacks, address changes, and delivery disputes should stay with an agent.

8. Return-policy questions

Policy questions are automatable when the article covers the product, region, time window, condition, and next step. Exceptions need a person because they may involve judgment and goodwill.

9. Channel setup instructions

Setup questions work well when the documentation lists prerequisites and a tested sequence. Protodesk, for example, focuses on email, WhatsApp, and live chat; the answer should stay inside the documented channel workflow.

If verification, permissions, or external-provider status differs from the article, the system should preserve context and hand off.

10. Known-error troubleshooting

The best troubleshooting candidates have a specific error signature, a reversible fix, and a confirmation step. The reply should explain how the customer can tell whether the fix worked.

Escalate after one unsuccessful attempt instead of repeating the same steps.

A reusable auto-resolve test

Before enabling any example, ask:

1. Is there one current source that fully answers the question?
2. Can the system identify the customer’s exact intent?
3. Is the answer safe without account-specific judgment?
4. Can the customer easily reply or reopen?
5. Is there a named human queue for every failure condition?

If any answer is no, use AI triage or an AI sidekick draft instead of auto-resolve.

Next, read the AI auto-resolve implementation checklist, audit the knowledge base requirements, or review the core definition of automated ticket resolution.