Agile delivery forces a constant tension between speed and quality.
This session bridges the gap, showing how to embed Gen-AI into the active testing lifecycle.
We will explore practical applications: assisted test design from specifications, 'four-handed coding' for E2E scripts, and delegating code optimization to AI.
Finally, we'll address cultural adoption, team resistance, and the concrete KPIs showing how an AI-augmented cycle helps teams consistently deliver excellence.

Target Audience: QA Leads, Software Architects, Senior Developers, and Test Managers.
Prerequisites: Solid understanding of Agile delivery cycles and QA processes. No advanced AI or specific programming language expertise is required to follow the core concepts.
Technical Requirements: Standard projector/screen for slides (16:9 format) and clicker. No risky live-coding is planned, but real architectural diagrams and code snippets will be presented.
Preferred Duration: 40-50 minutes (including 10 minutes for Q&A).
Additional Context: This proposal is driven by a real-world, large-scale enterprise case study. It focuses on practical implementation and measurable results (such as coverage metrics and regression times) rather than high-level theoretical concepts.