Customer support is one of the most mature use cases for enterprise AI agents, with enough real deployment history now to say clearly what actually works.
Triage and routing, correctly categorizing and directing incoming requests. Well-documented, repetitive questions with clear, consistent answers. Initial information gathering before a human agent gets involved, cutting the time spent on preliminary back-and-forth.
Genuinely novel problems without a documented answer, real frustration or escalation, and anything where a wrong answer carries real consequences still benefit from a clear, fast path to a human. A support system that traps frustrated customers in an agent loop with no escape does real brand damage.
Our full autonomy risk guide covers the underlying principle: set autonomy based on reversibility. In support specifically, a clear, easy escalation should exist from the start, not be added after a visible failure.
The real measure of a good deployment is how gracefully it hands off cases it can’t handle, not how few humans it needs on paper. See McKinsey’s own research on enterprise AI adoption.
