AI-Powered Incident Management: From Impact Assessment to Documentation

About the Session

In modern IT ecosystems, rapid and accurate incident severity assessment is essential for reducing business disruption. This talk explores how AI augments incident management not by simply detecting incidents, but by streamlining severity evaluation and automating the documentation process from start to finish. Using historical incident patterns, real-time telemetry, and system dependency graphs, AI models assign severity levels grounded in actual business impact. These assessments dynamically adapt as conditions change, factoring in customer sentiment, revenue exposure, and SLA compliance. The result is consistent, objective prioritization that removes manual guesswork. Additionally, the session covers AI-driven documentation tools that use advanced NLP and transcription techniques to capture user reports, support tickets, and incident response logs. These systems create enriched, time-stamped narratives of each incident’s lifecycle, preserving knowledge and accelerating future resolutions. Attendees will walk away with a practical framework for integrating AI into incident workflows and insights into addressing challenges like data quality, model bias, and system integration. Benefits include reduced MTTR, stronger operational resilience, and improved customer satisfaction.

Speaker

Naveen Kumar Chandu

Jawaharlal Nehru Technological University, India