AI customer support uses a branded AI employee as the first line: it answers questions from the business's own documentation, handles order and status enquiries, and escalates anything outside its scope to a human with the full conversation attached. The measure of success is resolved-or-escalated-cleanly, never a deflection number.
Support goes wrong when the assistant tries to hold a conversation it is not equipped for. Each operator is given an explicit scope and an explicit escalation trigger — refunds, complaints, safety, anything ambiguous — and it uses them.
A high deflection rate that leaves customers stranded is worse than no automation. The useful metric is whether the customer got a correct answer or reached a human quickly with their context intact.
Escalation reasons are the improvement backlog. When one topic escalates repeatedly, that topic needs better source material — not a broader prompt.
It answers from supplied first-party material and escalates when it lacks a grounded answer, rather than improvising.
Only what the business connects and permits. Data access is scoped per deployment.
The human receives the full transcript and context so the customer never repeats themselves.
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