If you step into a modern QA team today, you might not immediately see the change. People still review requirements, analyse risks, discuss defects. But look a little closer and something subtle is happening: AI is running alongside them, suggesting test ideas, rewriting brittle selectors, clustering logs, offering insights before anyone even asks.

In conversations about AI governance, the terms often sound big and abstract: fairness, transparency, accountability, robustness. But inside real projects, the work is far more grounded.

At the 2026 Swiss Testing Day sessions, a theme emerges again and again: modern QA must stretch beyond models, metrics, and pipelines. Testers increasingly find themselves in conversations about responsibility, inclusion, and trust. It is no longer enough to validate that a model works – we need to understand for whom it works, and for whom it doesn’t.