Why AI-powered testing needs to go beyond writing scripts and fixing broken tests

​You use AI to generate tests, identify and fix locators and hope that it works. But has it actually made software testing better?

​You are still dealing with the same problems: broken scripts after application updates, hours spent on maintenance, and bugs slipping through despite high test pass rates.

​Generating more tests doesn't solve these problems. And in complex enterprise environments, where a single business process can involve multiple applications, fixing locators and approving them is creating even more work than just fixing them yourself.

​So, what needs to change?

​In this webinar, Tobias Müller, shows you how TestResults -as a testing vendor- uses AI internally and how this translates into day-to-day testing work. This gives you a complete testing strategy as well as a deep understanding of what is coming next and what not!

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​We discuss 3 topics.

​- Success. Define the meaning of success with GenAI instead of 1000s of tests

​- Real computer-use. How to use hyper-localized UX models that are trained on your internal interfaces.

​- Test coverage vs. risks. Why having more tests doesn't necessarily mean you're covering the right risks.

​Who should join?

​QA managers, test leads, automation engineers, and anyone responsible for testing complex enterprise applications, especially in banking, insurance, and fintech.

​Join us on November 18 at 3:00 PM CET to discuss what's working, what isn't, and where Cognitive AI could make a practical difference in software testing.