In the context of cloud-based software development on Amazon Web Services (AWS), adopting DevOps practices through services like AWS CodePipeline is essential for ensuring Continuous Integration (CI) and Continuous Delivery (CD) while maintaining high software quality standards. However, integrating automated testing within these pipelines can be complex, particularly when aiming to generate comprehensive, high quality tests with good overall coverage. To address this challenge, this study proposes leveraging AI-driven test generation techniques within DevOps pipelines on AWS CodePipeline, followed by a manual approval phase for the generated tests. The primary objective of this research is to explore the use of Artificial Intelligence (AI) for automated test generation to optimize DevOps practices, enhance software quality, and accelerate release cycles.