How can AI testing help improve software quality while reducing manual effort?

General Discussions
1

I’m exploring AI testing tools and trying to understand their real benefits in software development. I’m particularly curious about how AI-driven testing can help improve overall software quality while also minimizing the need for extensive manual testing.

Specifically, I’m looking to understand:

  • How AI testing can detect bugs or regressions more effectively than traditional testing
  • Ways it can reduce repetitive manual testing tasks
  • How AI can help maintain and update test cases automatically (self-healing tests)
  • Any real-world examples of productivity gains or quality improvements from AI testing

Has anyone used AI testing tools in their projects? I’d love to hear how it impacted your testing efficiency and software quality.

2

AI testing automates repetitive tasks and predicts high-risk areas in code or UI, which reduces the need for manual regression testing. Candidates should describe how AI identifies patterns in past defects to prioritize tests, leading to higher defect detection rates and less human effort.

3

Self-healing capabilities minimize maintenance of test scripts. Candidates could explain how AI updates locators or workflows automatically when the application changes, preventing test failures due to minor UI modifications and reducing time spent on script updates.