AI-driven testing in practice: from requirements to reliable automation
See where AI genuinely helps, where it doesn’t, and how testers can stay firmly in control
AI is rapidly changing how software is built but most testing teams are still unsure how to use it safely, effectively, and at scale.
This masterclass cuts through the hype and focuses on practical, real-world AI testing workflows that teams can apply immediately.
We’ll walk through how modern QA teams can use AI to go from requirements → test cases → automation → reporting, while maintaining trust, traceability, and engineering discipline.
Attendees will see where AI genuinely helps, where it doesn’t, and how testers can stay firmly in control.
By the end of this session, attendees will be able to:
- Understand where AI fits (and doesn’t) in the modern QA lifecycle
- Design an AI-assisted testing workflow that starts from requirements and ends in automation
- Identify risks, limitations, and guardrails when using AI-generated tests
- Apply practical techniques to validate, trust, and improve AI outputs
- Confidently discuss AI testing approaches with developers, leaders, and stakeholders
