The agentic SOC—Rethinking SecOps for the next decade

Every major shift in cyberattacker behavior over the past decade has followed a meaningful shift in how defenders operate. When security operation centers (SOCs) deployed endpoint detection and response (EDR)—and later extended detection and response (XDR)—security teams raised the bar, pushing cyberattackers beyond phishing, commodity malware, and perimeter‑based attacks and into cloud infrastructure built for scale and speed. Read the new whitepaper—The agentic SOC: Your teammate for tomorrow, today That pattern continued as defenders embraced automation and AI to manage expanding digital estates. SOCs were often early scale adopters—using machine learning to reduce noise, improve visibility, and respond faster across growing environments. Cyberattackers became more targeted and multistage, moving deliberately across identities, endpoints, cloud resources, and email, where detection was hardest. Success increasingly depended on moving fast enough to act before analysts could connect the dots. Even with this progress, security operations (SecOps) still feel asymmetrical: threat actors only need to be right once, while defenders are judged by every miss. If defense depends on human intervention to begin, defense will always feel asymmetrical. To change the outcome, SOCs must change how defense itself works. This is the agentic SOC: where security delivers adaptive, autonomous defense, freeing defenders for strategic, high‑impact work. In this series, we’ll break down what that shift requires, what early experimentation has taught us, and where organizations can start today. Read more about how some organizations moving toward the agentic SOC and access a foundational roadmap for this transformation in our new whitepaper, The agentic SOC: Your teammate for tomorrow, today . What we mean by “the agentic SOC” At its core, the agentic SOC is an operating model that shifts security from reacting to incidents to anticipating how cyberattackers move—and actively reshaping the environment to cut off their paths. It brings together a platform that can increasingly defend itself through built-in autonomous defense, with AI agents working alongside humans to accelerate investigation, prioritization, and action—so teams spend less time on execution and more time on judgment, risk, and the decisions that matter. How does that change day-to-day work? Imagine a credential theft attempt. Built-in defenses automatically lock the affected account and isolate the compromised device within seconds—before lateral movement can begin. At the same time, an AI agent initiates an investigation, hunting for related activity across identity, endpoint, email, and cloud signals, and correlating everything into a single view. When an analyst opens their queue, the “noise” of overwhelming alerts is already gone. Evidence has been pre-assembled. Likely next steps are suggested. The analyst can start right away by answering higher impact questions: Is this part of a broader campa