MCCM Wiki
Helpdesk side-car AI patterns
A helpdesk side-car keeps the ticket system as system of record and uses AI beside it for drafts, summaries, and routing suggestions that an agent must accept. Replacing the ticket database with a chat log is not a pattern. It is an outage waiting to happen.
Vendors love “AI-native helpdesk.” Most SMEs already have a desk that works. The win is a side-car that returns hours without rewriting your case history.
Side-car means beside, not instead
Tickets, statuses, and SLAs stay in the helpdesk. AI reads allowed fields, proposes a reply or a queue, and writes back only through the agent action. That preserves audit trails and permissions you already paid for.
Three jobs that earn their keep
Draft replies from a knowledge snippet, summarize long threads for handoff, and suggest a queue with a confidence the agent can ignore. Each job needs a named human review gate before the customer sees text (same discipline as GDPR-safe AI workflows).
KPIs that matter
Primary: time to first reviewed reply, or time to correct queue. Secondary: reopen rate and misroute rate. Speed without those secondaries is a vanity metric. See AI pilot KPI examples.
Data rules
Redact secrets before prompts. Prefer vendor modes that do not train on your tickets. Document retention. If the vendor cannot answer the four classic questions on data, do not connect production cases.
Pilot shape
Six to ten weeks, one queue, one owner, rollback ready. Expand only after the primary KPI moves and agents want to keep the side-car.
Related
AI pilot · What an AI audit should deliver · From audit to pilot