What’s harder, getting AI tools adopted or building trust in their outputs?
How do you see QA evolving in 5 years with AI embedded in pipelines?
In 5 years, will QA engineers be called “AI Quality Trainers” instead?
What core QA skills remain essential even when AI-driven testing tools are introduced?
How can QA teams strike the right balance between leveraging AI for automation and retaining human critical thinking in testing?
Pertaining to AI in QA, how do you address switches between survival and thriving, when these experiences can change very quickly from day to day?
What’s the biggest challenge QA professionals face in adapting to AI-infused workflows?
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?
How to cope up with evolution of AI era?
What first steps would you recommend a complete beginner to AI take?
What skills should QA professionals develop today to remain relevant in an AI-driven testing future?