Shift Left QA for AI Systems. Catching Model Risk Before Production

This blog advocates Shift Left QA for AI systems, arguing that traditional, UI-centric testing misses upstream risks and promoting early validation of datasets, prompt testing as business logic, pre-UI model behavior evaluation, and continuous drift monitoring; it offers real-world examples, key metrics beyond accuracy, and guidance on governance, explainability, and ownership to reduce bias, compliance exposure, and costly rework while enabling safer, faster releases.