Yes. Tagging and routing are high-volume, easy to check and cheap to reverse, so an agent can do them at depth 3 once certified on your own past tickets. People own the categories and routing rules, review the tickets the agent is unsure about, and fix misroutes. Complaints, fraud and vulnerability are caught first.
Why is this a good job for an agent?
A misrouted ticket costs time, not money. The receiving team sends it back or on, and the customer waits a little longer. That makes the work reversible in a way refunds and account changes are not.
It is also measurable. Every ticket ends up in a final queue with a final set of tags, chosen or corrected by the people who handled it. Compare the agent's choices against those and you have a running accuracy measure, by category, with no extra effort.
What conditions make it work?
- A defined set of tags, owned by a named person and kept short enough that people use it consistently.
- Routing rules written by people: which tags go to which team, in what order.
- A confidence threshold, below which the ticket goes to a general queue for a person to triage.
- Priority categories caught first: complaints, possible fraud, vulnerability, legal threats and safety. A ticket that is both a billing question and a complaint is a complaint.
- Multi-issue tickets split or linked, so the second request in an email is not lost.
What may the agent do, and what stays with a person?
| Task | The agent | A person |
|---|---|---|
| Apply tags from the set | Tags each ticket | Reviews samples |
| Route by the rules | Routes to the right queue | Owns the rules |
| Low-confidence tickets | Sends to the general queue | Triages |
| Split a multi-issue ticket | Creates linked tickets | None |
| Detect complaints and vulnerability | Tags and routes with priority | Handles |
| Acknowledge the customer | Sends an acknowledgement with the queue's response time | None |
| Change tags or rules | Proposes changes from patterns | Approves |
The step-by-step methods are in how to tag and categorise support tickets with an AI agent and how to route support tickets to the right team with an AI agent.
What does the customer see?
Usually just an acknowledgement: their message has arrived and when to expect a reply, based on the receiving queue's real response time. The tags themselves stay internal. That matters for one category in particular. A ticket tagged for the financial crime team must not trigger anything the customer can see that hints at suspicion, which rules out acknowledgements that differ for those tickets.
What does this look like in practice?
Take a home insurer's support inbox. One email says: the customer's roof was damaged in a storm, they want to make a claim, they have also moved house, and they are unhappy that nobody answered their call yesterday.
The agent finds three issues. It tags the email as a new claim, routes it to the claims team as the main ticket, creates a linked task for the address change, and logs a complaint about the unanswered call to the complaints queue. The customer receives one acknowledgement covering all three. A different email, a single line with an attachment and no clear request, falls below the confidence threshold and goes to the general queue, where a person reads it.
Which controls make it safe?
- Certification on your own past tickets, scored by category, with complaints and vulnerability weighted heavily.
- A fallback queue for low-confidence tickets.
- Priority categories detected before any other routing.
- Weekly review of misroutes and of tags people corrected.
- Every routing decision filed with the tags and confidence.
Routing works better when the agent knows the customer's history; see whether a support agent can read a customer's previous tickets. Deciding what goes first is covered in whether an AI agent can prioritise urgent tickets, and the wider approach in the guide to AI customer support agents.
Questions people ask
What if the tag set changes?
Update the agent's brief and sources, then retest on recent tickets before the new set goes live. The model itself does not need retraining.
Should the agent route straight to individuals?
Usually to queues. Routing to named people creates gaps when they are away, unless the rules handle absence.
How accurate does routing need to be?
Accurate enough that teams trust it, and close to perfect on complaints and vulnerability. Measure misses on those categories separately.