Experts like Ben, Garie, and Jammie will explain how AI transforms quality engineering. 
Discuss the evolving trends, processes, and roles, and address challenges and biases in AI models.
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Hi there,
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How should we change our career best to be relevant in this new market?
What key skills should testers and developers prioritize to stay relevant in quality engineering as AI continues to reshape roles and processes within organizations?
What roles are suitable for a QA/Tester to transform into with AI taking over much of testing?
What do each of the panelists think about how Automated QA will look in 1…5…10…years from now?
How much of the industry do you approximate that have AI integrated in their processes, especially the QA branch?
In what ways can AI-driven tools enhance the accuracy and efficiency of quality assurance processes, and what are the limitations?
How will AI in testing transform the various specialities of testing like Performance testing, Accessibility testing, Usability testing, etc.?
What qualifications (such as with AI comfort level and experience) do you feel a quality engineer may need to have by 2025 or 2026?
What new skills and knowledge should quality engineers acquire to stay relevant in the age of AI?
Where to train ourselves for testing AI models?
What is the job outlook for testers 5 years down the line?
Can we even ever hope to create AI that is TRULY without biases?
How has the rise of AI changed the responsibilities and focus of quality engineering teams?
How can we train AI agents to learn the business to help produce meaningful use cases to test?
Beyond AI, what other disruptive trends might change quality engineering in the present and future?
Suggest some AI tools/ Git/ Maven Repos to explore and integrate Gen AI with Selenium or Playwright.
Which single disruption or impact is the most significant for quality engineering (in the age of AI)?
Which industries may be most affected in quality testing due to the expansion of automation and AI in the testing space?
