AI-Powered DevOps: Leveraging machine intelligence for seamless CI/CD and infrastructure optimization

AI integration into DevOps practices clearly assumes a giant leap forward in the effective, reliable, and even more elastic delivery of software. This work focuses on the application of artificial intelligence and machine learning in improving CI/CD practices, infrastructure, and software engineering processes. AI plays a major role in reducing the possibility of human errors and greatly improves the speed at which the development of systems is conducted thanks to the automation of activities like testing, resource tracking, and identification of abnormalities. Examples from Netflix, Google and other enterprises show how Predictive Analytics, Intelligent Deployment Strategies and Automation of Code reviews changed the facet of integrated software delivery. However, the complexity of integration, poor data quality, and organizational change resistances form part of the evaluation together with the benefits. From here, the work showcases how AI plays a pivotal role in optimizing DevOps, meeting infrastructure requirements flexibly, and how the integration empowers multiple teams when constructing the future of software engineering.