AIOps differs from traditional IT Operations by moving from a manual, reactive approach to an intelligent and proactive one. Traditional ITOps relies on monitoring tools, rule-based alerts, and responding after issues occur, while AIOps uses machine learning to analyze large volumes of data from logs, metrics, and events to detect anomalies early and predict potential problems. This improves efficiency, speeds up incident response, and supports better decision-making. The main benefits of AIOps include reduced downtime, faster problem resolution, and improved system performance, while challenges may include tool complexity, data quality issues, and the need for skilled professionals to manage AI-driven systems.