After AI Coding enters the testing team, who guarantees test quality while test efficiency improves?

AI Coding has greatly increased the speed of generating test scripts and test cases, but AI-generated test cases may miss critical business branches, and automated scripts may also make CI turn green by extending wait times or lowering assertion standards, while real defects still exist. Testing teams need to split AI test case generation into three stages: requirement decomposition, risk analysis, and manual review, and divide the permission boundaries for AI Agent operations into read-only analysis, controlled modification, controlled execution, and manual approval. AI can shorten troubleshooting time, but the root cause of defects and the effectiveness of fixes must be confirmed through reproduction and verification.