AI integration into regression testing significantly enhances software quality by automating and optimizing the testing process, addressing challenges such as time consumption and resource intensity associated with traditional methods. AI tools analyze user behavior, code changes, and defect patterns to prioritize and generate test cases, predict high-risk areas, and adapt test scripts dynamically, thereby minimizing maintenance efforts and enhancing defect detection. Platforms like KaneAI, ACCELQ, and Katalon Studio offer features like self-healing scripts and multi-language code export, streamlining the testing process and reducing the need for extensive coding expertise. As AI continues to evolve, autonomous testing agents are anticipated to advance further, making regression testing more adaptive, intelligent, and efficient, ultimately transforming the landscape of software testing with increased speed, accuracy, and reliability.