Customer Support Automation

Customer Support is one of the areas where AI has the fastest measurable ROI. 3 classic use cases, by order of difficulty: **deflection** (the AI answers directly if possible), **triage** (the AI routes + categorizes), **agent copilot** (the AI pre-drafts the human's answer).

**Deflection with RAG**: FAQ bot grounded on your product docs + past tickets. Reads the user question, searches the knowledge base, produces an answer with source citations. Works well for known questions (passwords, billing, product features). Fails on account-specific or empathy-required issues — those should be escalated to a human immediately, not the model trying its luck.

Triage: incoming ticket → classifier decides (a) urgency (urgent / normal / low), (b) category (billing, technical, account, ...), (c) sentiment (angry / neutral / happy), (d) complexity (auto-resolvable / needs human). This feeds the routing: priority queue to a senior agent, low-priority queue to the deflection bot.

**Agent copilot**: the human agent opens a ticket, the AI has already (a) summarized the customer history, (b) pulled relevant KB articles, (c) drafted 2-3 suggested responses. The agent validates/edits/sends. Result: 30-50% faster resolution, better consistency.

**Metrics that matter**: **deflection rate** (% tickets auto-resolved without agent), **CSAT on AI answers** (did it really help?), **escalation quality** (did the AI escalate the right ones?), **Time-To-Resolution** for cases treated by copilot. Vanity metrics: 'number of messages exchanged' — doesn't say quality.

Warning — the ceiling: pure chatbot with no human alternative = poor experience for 10-20% of real problems. ALWAYS offer 'talk to a human' access. Gains come from automating the repetitive 60-70%, not from replacing all support.