AI code review employs artificial intelligence algorithms to evaluate software code for errors, bugs, potential security vulnerabilities, performance issues, or best practices violations, analyzing patterns and structures to identify these issues, allowing developers to address them earlier in the software development cycle. AI code reviews improve overall quality by detecting issues like security vulnerabilities, code smells, performance bottlenecks, and more, reducing opportunities for human error by leveraging machine learning techniques, boosting developer productivity by freeing time from manual code review tasks, and finding known and unknown issue types with static application security testing (SAST) and dynamic application security testing (DAST). The AI code review process is enhanced by a feedback loop of improvement as the algorithm learns with the developers, creating an accurate and effective code review process that combines speed, efficiency, and human judgment.