Agentic SOC: How Security Teams Cut Alert Noise and Decide Faster Against AI-Powered Threats
AI-assisted attacks are compressing the time security teams have to understand what is happening and decide what to do next. Meanwhile, many SOCs still rely on analysts to manually triage growing volumes of alerts, slowing the path from detection to action.
More alerts and more data have not closed that gap. A high alert count tells a team its sensors are running, not which intrusion to work first.
In this session, see how an operationalized intelligence powers an agentic SOC and suppresses low-value alerts before they reach a queue, shortens investigations, and turns retained security data into decisions an analyst can defend in a review.
Learn how combining agentic AI, operationalized threat intelligence, and a unified security data foundation gives analysts context at the moment an event lands rather than three tools later. Agents take first-line triage and enrichment. Analysts supervise, approve, and own escalation, and every agent action is logged, explainable, and reversible.
What You’ll Learn
- How AI-assisted intrusions change what a SOC has to accomplish in the earliest stages of an attack
- Why adding alert sources and storage does not produce better decisions
- How agentic AI shortens triage and investigation while analysts keep the final call
- Why an agent inherits every flaw in the data it is given, and what OCSF normalization, deduplication, and intelligence fusion at ingest fix
- What governed action looks like in practice: every automated response logged, explainable, and reversible