Intelligent Automation and Predictive ITSM for Service Optimisation
Annotatsiya
Traditional ITSM has become reactive, manual, and expensive with the growing complexity of the environment within the enterprise IT. This paper outlines an all-inclusive model of intelligent automation and predictive analytics as a way to streamline ITSM operations, ensure reliability of services, minimise outages, and streamline overall operations. A thorough literature review presents an overview of how artificial intelligence (AI), machine learning (ML), natural Language Processing (NLP), and predictive modelling have been applied to ITSM functions. The technical model that is proposed will utilise event-based automation, anomaly-based analysis, and foreseeing incidents with the help of ML-based algorithms. Experiment simulations reveal a steep improvement in incident resolution time, proactive identification of issues, and availability of services in general. High degrees of predictive incident resolution are made possible by the model with very low false negatives. The study provides a versatile journey to organisations interested in modernising ITSM with intelligent automation and predictive features.