Integrating Artificial Intelligence with DevOps: Enhancing continuous delivery, automation, and predictive analytics for high-performance software engineering

Abstract

AI-DevOps has become a major innovation in managing the increasing levels of software engineering complexity. This study aims to reveal how AI shall be integrated into major DevOps patterns and the CD, automation, and predictive analysis processes to improve performance in software engineering. When deploying AI and machine learning, NLP, and predictive modeling in CI/CD, organizations gain an opportunity to enhance the CI/CD pipeline, facilitate the automation of monotonous tasks, and address possible deviations. The paper also explores the barriers to AI adoption in the DevOps environment from the technical, organizational, and ethical perspectives. Based on a review of the studies, cases, and observations of trends in the DevOps field, this research outlines the possibilities for utilizing AI for enhancing the innovation of DevOps and proffer prescriptive strategies for doing so. The results advance the understanding of intelligent, adaptive, and efficient DevOps ecosystems that help fulfill the needs of modern software delivery.