Automated Quality Assurance in Customer Service: Challenges, Implementation, and Use Cases
In this session, we demonstrate how AI-based quality assurance can be implemented in real contact center operations with minimal integration effort and full managerial control. Using real examples from QAWacht, we show how automated QA works end-to-end—from call analysis to dashboards and governance.
Topics we’ll cover:
- Live and recorded call analysis with up to 100% coverage
- Transparent AI-based quality scoring with human review and correction
- Dashboards with drill-down from KPIs to individual conversations
What you’ll take away from the session:
- A clear understanding of how automated QA can replace sample-based controls
- Practical insight into implementation effort, risks, and timelines
- Concrete use cases across quality management, compliance, coaching, and audits
- Learn how to scale QA without increasing headcount
- Gain a concrete business process view of using AI-based QA in contact center operations
- See how AI can support — not replace — human responsibility in QA decisions
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