International Journal on Science and Technology

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Challenges in Traditional Incident Management: The Case for AI-Driven Solutions

Author(s) Lakshmi Narasimha Rohith Samudrala
Country United States
Abstract Incident management is a critical function of IT operations. It ensures organizations are able to maintain their systems reliably with minimal service disruptions. Traditional incident management approaches rely on reactive monitoring, manual root-cause identification, and static threshold-based alerting. This leads to a delay in detection of the issues, prolonged resolution times, and increased operational costs. As IT environments grow more complex organizations struggle with alert fatigue, siloed monitoring, and slow incident response. This results in financial losses, reputational risks, and compliance challenges.
This paper explores the limitations of traditional incident management and the impact it has on organizations. The paper introduces proactive incident management and compares it to the traditional approach of incident management. It also further explains how proactive incident management leverages AI-based solutions to remediate the limitations of traditional incident management.
Finally, the paper emphasizes the need for AI-driven solutions in incident management.
Keywords Incident Management, IT Service Management (ITSM), Mean Time To Detect (MTTD), Mean Time To Resolve (MTTR), Service-Level-Agreement (SLA), AI-Driven anomaly detection, AI, Machine Learning, Adaptive Baselining, Static Thresholds
Field Engineering
Published In Volume 15, Issue 2, April-June 2024
Published On 2024-05-09
Cite This Challenges in Traditional Incident Management: The Case for AI-Driven Solutions - Lakshmi Narasimha Rohith Samudrala - IJSAT Volume 15, Issue 2, April-June 2024. DOI 10.71097/IJSAT.v15.i2.2838
DOI https://doi.org/10.71097/IJSAT.v15.i2.2838
Short DOI https://doi.org/g899gc
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