AI for customer support

About this course

This course is about using AI in customer support so answers get faster and more honest, not a bot that lies with confidence. It solves the problem of a growing ticket volume with too few people to handle it, while the knowledge base and answer quality lag behind what customers actually ask.

The course moves from ticket flow and metrics that don't lie, to building a knowledge base from chats and tickets, writing answers and templates that don't feel canned, automation and routing with an honest 'I don't know' from the first-line bot, and a quality system: a scoring rubric, spot audits, and training new hires on real tickets.

It's for people who run or work in support and want to bring in AI without losing answer quality. You'll need access to a real export of tickets and conversations — the tasks are built on them, not on made-up examples.

What you'll learn

• Classify the ticket flow by type, frequency, and cost of error
• Build knowledge-base articles on a structure a model can actually use
• Track support metrics that don't lie (first-contact resolution, repeat contacts)
• Draft answers with AI, with mandatory human review
• Build templates and routing rules that don't feel canned
• Define the first-line bot's boundaries and an honest "I don't know"
• Score answer quality against a rubric and run spot audits
• Protect customer data privacy when working with AI

What you'll end up with

• A knowledge-base core covering the ten most frequent topics, ready to use
• A library of answers for fifteen frequent scenarios with templates
• A designed first-line automation loop with confidence thresholds
• A quarterly quality system: a scoring rubric and a spot-audit plan, plus a certificate on paid plans

Not for people looking for a turnkey chatbot — this is about building the process and knowledge base so a bot doesn't end up lying.