An AI chatbot engages customers in text-based (or occasionally voice-based) dialogue and attempts to answer questions, complete tasks, or route requests without human intervention. Unlike rule-based bots that follow rigid decision trees, AI chatbots use machine learning and natural language processing (NLP) to interpret intent and generate contextually relevant responses.
For support teams, key capabilities to evaluate include:
- Intent recognition accuracy — how reliably the bot understands what customers are asking
- Fallback and handoff logic — how gracefully it transfers to a live agent when it cannot help
- Integration depth — whether it can look up orders, reset passwords, or take actions in backend systems
Performance is commonly tracked via containment rate (the share of conversations resolved without agent involvement), CSAT on bot interactions, and false-positive escalation rate. An AI chatbot that deflects effectively but frustrates customers is a net negative — both metrics must be monitored together.