Leveraging AI Models for Proactive Problem Detection, Investigation, and Root Cause Analysis in Enterprise IT Infrastructure

In today's fast - paced digital landscape, the continuous availability and optimal performance of enterprise IT infrastructure are non - negotiable. Yet, managing the increasing complexity and dynamism of modern IT environments, which span networks, systems, applications, and cybersecurity, poses significant challenges for traditional monitoring solutions. These legacy systems, reliant on static, hard - coded thresholds and manual data correlation, often lead to reactive problem identification, overwhelming alert fatigue, and prolonged incident resolution times. This directly impacts business continuity, user experience, and operational efficiency, with many organizations still facing Mean Time To Resolve (MTTR) figures often exceeding several hours for critical incidents. This white paper outlines a transformative approach: leveraging Artificial Intelligence (AI) models to revolutionize the way IT problems are detected, investigated, and their root causes identified. By intelligently augmenting human capabilities in problem management, AI empowers organizations to build more resilient and efficient IT operations. Industry reports suggest that organizations adopting AIOps can see a reduction in Mean Time To Detect (MTTD) by as much as 25 - 40% and a decrease in MTTR by 30 - 50%. Our proposed framework highlights how AI models perform two critical functions: 1) Sophisticated Problem Detection: AI models use advanced machine learning mechanisms to learn