What is the ROI of investing in AI-powered testing?
What are the ethical considerations when using AI in testing, especially regarding bias in test data and the potential impact on end-users?
How can it be more practical in real life???
What sort of adaptive learning are AI models that are used in testing being trained on that will make them more powerful, ubiquitous - or always-on and everywhere needed?
Vikash: I’ve seen AI update tests by finding elements that have small textual changes. Like “Add To Cart” changes to “Add To My Cart” and the AI updates the new object reducing maintenance.
Are there certain types of testing that you believe AI will never be able to handle effectively? If so, why?
How ai can fasten automation?
Should testers expect a compromise in capability or speed (or another metric) in omnipresent AI-powered testing?
How can QE skill themselves, can you talk about one practical scenario?
Strictly from the testing perspective, given the omnipresent potential, are we closer to a kind of AI capability approaching AGI?
Could you please bring some examples or best practices?
Are there any tools to test AI?