Can AI-driven automation ever fully replace exploratory testing, or will that remain inherently human?
Who is accountable if an AI system misses a critical defect — the AI, the engineers, or the enterprise?
Can AI truly understand user experience and business context, or will it always miss the “human touch” in testing?
How can we augment AI to do more human based testing like user experience, Accessibility etc , is it recommended to use AI there?
With AI tools now automating many testing tasks, how relevant is it to still learn traditional automation frameworks like Selenium or Rest Assured?
Should QA professionals focus more on AI-driven testing, or balance both, and if so, how?
Can AI truly understand business context well enough to design meaningful tests without human input?
If AI handles 100% of test automation, what role should human testers play?
Should enterprises prioritize speed (AI-generated automation) over control (human-designed tests)?
Who is accountable if an AI-generated test misses a critical defect in production?
What are some of the less obvious but impactful areas where AI could augment human testers’ capabilities, allowing them to focus on "more complex aspects of software quality?
Could AI evolve to not just automate tests, but also decide what to test next?
If AI achieves near-100% automation, does manual validation still have a place?
Will testers transition from writing scripts to training AI for better test outcomes?
How do you see AI impacting exploratory testing, where creativity plays a major role?
What’s scarier: flaky human-written tests or flaky AI-generated ones?
Should AI be treated as a teammate in QA or just a tool?
How important it is to have human interventions in automations and not completely rely on what AI does or outputs?
How do we ensure accountability when an AI-written test misses a critical bug?
When would you look at adopting AI in an organization that hasn’t yet implemented automated testing? Automation first, then AI? Both concurrently?