Test automation often fails due to a lack of shared structure across teams, leading to unmanageable test suites and a loss of trust in the system.
The automation trap occurs when unstructured automation amplifies complexity and becomes a bottleneck instead of accelerating delivery.
The Quality Tree Framework provides a structured, systems-thinking model for growing quality capabilities step-by-step across an entire organization.
The framework is built on three dimensions: eight branches for core IT areas, nine maturity levels for evolution, and 90 quality nodes for concrete capabilities.
For AI systems that automate decisions, a structured approach is essential for building trust, ensuring robustness, and implementing effective governance.
A lack of quality structure leads to slow releases, high maintenance costs, and reduced competitiveness, problems that cannot be solved by simply adding more tools.
The Quality Tree Application is a platform that makes the quality system visible, allowing organizations to assess maturity, identify gaps, and manage progress.
Automated accessibility testing serves as an example of how a capability evolves from a manual, inconsistent activity to a fully integrated and measurable system.
Applying the framework involves assessing your current state, focusing on targeted improvements, and scaling quality systematically to move from chaos to control.
Jobs that call for the skills explored in this talk.