The promise of an AI support agent is straightforward: resolve the questions that don't need a human, so the humans can handle the ones that do. Tools like Intercom's Fin read your help docs and past conversations, then answer customer questions directly in chat, citing the source material it used.
Where this genuinely works is high-frequency, low-ambiguity questions — shipping timelines, return policies, how a feature works, account basics. These are questions with a single correct answer that already exists somewhere in your documentation, and an AI agent can surface that answer instantly, at any hour, without waiting on a person.
Where it frustrates customers is anything emotionally loaded or genuinely ambiguous: a billing dispute, a complaint, a request that doesn't fit the documented cases. Customers can tell quickly when they're being looped by a bot that doesn't understand the actual problem, and that experience does more brand damage than a slower human reply would have.
The fix is structural, not technical: set the AI to resolve only the categories you trust it with, and make the handoff to a human fast and obvious the moment a conversation falls outside them. Done well, this setup can resolve a meaningful share of tickets without a customer ever feeling like they hit a wall.
Start narrow. Let the AI handle two or three question types you're confident it answers correctly, watch the transcripts for a few weeks, and expand its scope only as it earns that trust — rather than turning it loose on everything from day one.