Agentic AI for Autonomous Incident Prioritization and Intelligent Alert Correlation in Enterprise Monitoring Systems

Modern enterprise monitoring environments generate enormous volumes of alerts, telemetry streams, logs, and operational events from distributed infrastructure, cloud-native workloads, middleware services, virtualization platforms, and enterprise applications. This paper proposes an Agentic AI Framework for Autonomous Incident Prioritization and Intelligent Alert Correlation in Enterprise Monitoring Systems. The framework introduces specialized AI agents responsible for alert ingestion, noise reduction, telemetry aggregation, dependency correlation, severity classification, business impact assessment, escalation recommendation, and autonomous operational reasoning.