hem, the useful question is not whether a platform has AI, but what changes at thFor more than a decade, security information and event management (SIEM) has been the center of most security operations centers. A traditional SIEM collects logs from firewalls, endpoints, servers, and cloud services, stores them in one place, and runs correlation rules that raise alerts when known patterns appear. Analysts then work through those alerts, one queue at a time.<\/p>\n
That model still works, but it strains under modern data volumes. Cloud workloads, remote users, and SaaS applications produce far more telemetry than rule writers can keep up with, and analysts spend much of each shift on alerts that turn out to be harmless. AI-powered security operations aim to ease that load by learning normal behavior, ranking risk, and assembling context automatically.<\/p>\n
The difficulty is that almost every vendor now uses the word “AI.” For SOC analysts and the managers who lead te console during an ordinary night shift. This article looks at those practical differences, what AI does not replace, and how to test the claims before you commit.<\/p>\n