AI Customer Service Automation

Common starting points include opening hours, service coverage, order or request status, document requirements, policy navigation, appointment changes, and ticket classification.

Complex complaints, vulnerable customers, regulated guidance, refunds outside policy, and unclear identity should move to a person. Automation should shorten the path to expertise rather than hide it.

Create an owned support knowledge base with clear sources, review dates, and responsible authors. The system should cite or link to the relevant policy when that helps the customer verify an answer.

When sources conflict, are missing, or fall outside the allowed scope, the correct behavior is to ask a clarifying question or escalate. Confidence language is not a substitute for evidence.

Deflection can be misleading if customers leave without a solution. Review whether the issue was actually resolved and whether the customer had to return through another channel.

Human agents should be able to flag poor answers and missing knowledge. Those corrections create the feedback loop for improving content, routing, and model evaluation.