AI testing is shifting from test generation to maintenance and exploration

Recent vendor and practitioner signals emphasize AI’s potential to understand legacy systems, generate and update tests, explore unscripted paths, connect requirements to acceptance criteria, and reduce QA debt. The buyer-relevant message is that value comes from preserving release velocity and cutting upkeep, while claims about coverage and cost savings still require stronger measurement and human review.