AAMC partnered with AWS to build an intelligent, AI-driven contact centre that transforms data into actionable insights. The solution unifies customer interaction datacalls, chats, surveys, and QA reviewsinto a single environment where AI continuously analyses and learns. Leaders ask questions in natural language and receive instant, data-backed answers with visual context. This self-optimising system enables faster, more confident decision-making while continuously improving customer experience operations through deeper visibility and adaptive learning capabilities.
What this session is about
Playbook
Editorial commentary · what to actually do about this on Monday
The concept
Unified contact-center data — calls + chats + surveys + QA reviews. Natural language queries; instant answers with visuals. Self-optimising system.
Why it matters
Contact-center managers can't read everything that flows through the floor. AI compresses that.
The hard parts
Quality of insights depends on quality of data labelling. Garbage in, garbage out applies harder here than usual.
Playbook moves
(1) Tag conversations consistently. (2) Bad tagging breaks AI insights subtly. (3) Re-tag historical data when taxonomies change.
The surprise
The most useful contact-center AI insight isn't summary metrics — it's the *outliers*. The 3 calls that broke pattern reveal more than the 10,000 that didn't. Build the outlier-surfacing UX, not the summary dashboard.
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Independent editorial perspective — not an official AWS or speaker statement. Designed for executives evaluating what to brief their teams on next.