The Role of AI/ML in Modern DevOps: From Anomaly Detection to Predictive Operations
Ravindra Agrawal · International Journal of Computer Trends and Technology · 2025
Incorporating Artificial Intelligence and Machine Learning into DevOps practices is a fundamental shift in organizations' software delivery and operations. A 2024 DORA survey found that more than 81% of organizations are considering incorporating AI into their applications [1]. This deep analysis examines how AI/ML technologies revolutionize operational efficiency, incident response, and resource optimization within DevOps workflows. This study, by carefully analyzing the current applications and developing trends, proves that entities adopting AI-driven DevOps methodologies see considerable improvement in system dependability, cost efficiency, and team output while lowering operational expenditures and the rate of human error. The paper will also address some practical implications of this convergence, including barriers to implementation, performance indicators, and future pathways in the fast-developing sphere of AI-augmented DevOps. DORA metrics continue to be the key measurement criteria for measuring the success of AI/ML within DevOps.