Join our engaging panel discussion to gain valuable insights into the future of testing with the impact of AI in Quality Assurance and beyond.
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If you have already registered and up for the session, feel free to post your questions in the thread below 
Here are some of the questions poured in from the attendees:
I am assuming many openings we can expect in the upcoming days for testing the AI Tools, So how do QA’s start upskilling themselves to become an AI Tester?
We all know that there’s a difference between automatic and autonomous. I hear that an aspiration is to get to a state of being autonomous. However, do you see Generative AI achieving autonomy considering the biases and contexts?
Could you assist us with identifying some AI tools that could enhance our daily quality assurance tasks?
One challenge face as a QA tester is that most company managers find it had to adapt to new technology. They far, it will be a loss of funds and resources. What do we do, and how can we convince them?
What measures are being implemented to ensure data privacy and security, especially when AI is trained on sensitive or personal data?
How much can you rely on the results of AI for your context? Can you just plug and play the output of AI into your test framework?
How do you see AI (private LLM trained on private medical datasets) being used for medical product testing? Any suggestion for a verification and validation strategy for AI tool itself to use for medical products?
With mobile usage on the rise, is mobile app testing poised to become more crucial than testing for web-based applications in the foreseeable future?
AI has come to stay; if a QA Tester refuses to upgrade, those are the people AI will take their job. Not me.
What are your views on the assertion that testers will become obsolete as developers can handle testing duties as well?
How can we improve the explainability and transparency of Generative AI systems, especially in high-stakes scenarios like healthcare or legal decisions?
Will only acknowledging the bias help in cleaning the data? How about ethical considerations? Contexts? How do you eliminate the bias?
What kind of regulatory frameworks could be effective in managing the advancements and deployments of Generative AI technologies?
Hi Naveen and other experts, are there any proven concepts like playwright autoplay that exist for webdriverIO?
For complex automation projects how AI is going to help. I see simple solution through AI is working, but when you want to create a framework for complex projects and scenarios can we rely on AI
Will AI eventually take up the QA jobs?
What will be testing jobs regarding AI tester job?
How QA can be sure using AI whats is the health check we should have?
Can we get more insight into all the places we can implement AI in the Test framework?