Transforming Incident Management: Leveraging Artificial Intelligence for Enhanced Detection, Classification, and Resolution

Abstract

This research explores how artificial intelligence can fundamentally change the way enterprises handle incident management. As companies face increasingly complex IT environments, traditional manual approaches to spotting, categorizing, and fixing problems have struggled to keep pace with operational demands. By bringing together AI capabilities like machine learning for spotting unusual patterns, natural language processing for understanding automated reports, and predictive analytics for assessing problem severity, we can dramatically improve how efficiently incidents are managed. This investigation examines how AI-based approaches enable systems to automatically generate incident reports, make smart severity assessments, calculate changing impacts in real-time, and create thorough documentation through meeting transcription and summarization. While highlighting the benefits of increased speed, better accuracy, and improved scalability, this work also addresses real-world implementation hurdles including data quality concerns, potential algorithmic biases, and the complexities of integrating with existing systems. Companies that successfully implement AI-powered incident management solutions stand to gain stronger operational resilience, faster problem resolution times, and happier customers, giving them a competitive edge in our increasingly digital business landscape.