Why doesn't your contact center AI know what your best agents know?
On this episode, we ask why the knowledge top contact center agents have often never reaches contact center AI systems — and what it takes to build a feedback loop that captures it. The most valuable knowledge in a contact center lives in two places: call transcripts, and the people already excelling at the job. Reviewing call transcripts for quality and compliance is standard practice. But most of that review is built to flag what went wrong on a call. It rarely explains what worked, or why. What's needed instead is a structured, outcome-tied annotation layer built to explain why a call went well, turn by turn. Derek Brameyer, head of application engineering at TELUS Digital , draws on his work building this kind of annotation system for CX leaders. He explains why tying annotation to verified operational data rather than AI-inferred guesses is what makes it reliable enough to act on, and how that kind of feedback loop can be built with the interactions you already record and transcribe. Show notes Read Derek Brameyer’s latest article, Institutional knowledge is the missing layer in most contact center AI data strategies Listen to the Questions for now episode How can brands design and deliver seamless customer experiences?
