Artificial intelligence is advancing swiftly, putting cybersecurity leaders under significant strain to stay ahead. The optimal approach involves dividing cybersecurity into two distinct roles: one focused on AI-driven threat detection and another dedicated to enhancing incident response capabilities. At the forefront of these AI platforms lie tools such as Claude, Cursor, and Codex, where analysts, detection engineers, and incident responders work together with AI to address challenges, write detections, generate reports, search for threats, and make informed decisions.
An AI model requires endpoint telemetry, process trees, authentication logs, email history, threat intelligence, previous investigations, detection rules, and organizational knowledge before it can make an informed decision.
Rather than treating each alert as a separate inquiry with a sophisticated language model, a competent AI SOC integrates deterministic workflows, forensic analysis, organizational memory, cached context, and selective AI reasoning. Customers usually receive only escalated incidents and periodic reports without access to all evidence gathered along the way. Unlike being implemented overnight to replace Managed Detection and Response (MDRs), these systems enable organizations to take control over their investigation processes, safeguard institutional knowledge, and ultimately manage their security operations autonomously.
Join Itai Tevet, co-founder and CEO of Intezer, and Lital Asher-Dotan, chief marketing officer, for a candid discussion about how artificial intelligence is currently integrated into security operations today. Three key takeaways: 1.
