AI-Enhanced Customer Experience & Support Playbook (Chatbots, Assistants)

Three to five, chosen for high volume, low complexity, and strong existing knowledge-base coverage. A narrow, clean first wave builds the internal and customer trust needed to expand faster in later waves than a broad, rough launch ever does.

An unaudited or outdated knowledge base. The model itself is rarely the root cause of a bad customer experience — it's confidently surfacing wrong or contradictory source content, which is why the audit step comes before any intent goes live, not after.

Neither alone — track them together on the same wave scorecard. A rollout optimizing purely for containment routinely produces a CSAT decline that erases the cost savings once escalation calls, complaint handling, and customer churn are accounted for.

Assist mode is intent-specific and built into the same escalation framework as Deflect and Escalate, so the handling mode for any given contact is a deliberate classification decision, not left to whether an individual agent happens to open a separate co-pilot tool.

Configure escalation triggers — sentiment detection, repeated clarification requests, and an always-visible "talk to a person" option — that override the default intent classification and force a handoff, and make sure the human agent receives full conversation context so the customer never has to repeat themselves.