AI unit test generation is the process of using artificial intelligence to automatically create unit test scripts for software applications, streamlining the testing process and reducing manual effort. This technique can help teams generate a wider range of test cases, including edge cases, and provide better test coverage. AI-based unit test generation tools analyze code structure, detect possible edge cases, and create test cases automatically, while also providing features such as prioritization, debugging assistance, and integration with CI/CD pipelines. While these tools can save time and improve testing efficiency, they also come with challenges, including the need for high-quality training data, transparency in decision-making processes, and ongoing maintenance to retain effectiveness. By leveraging AI unit test generation, teams can optimize their testing process, reduce costs associated with manual testing, and improve overall software quality.