AI SOC Automation: From Manual Triage to Agent-Driven Operations
AI SOC automation is the shift from manually handling security alerts and investigations to using AI-driven agents that continuously triage, investigate, and remediate threats across the enterprise, allowing human analysts to supervise outcomes instead of performing every step themselves. That shift is no longer theoretical; it is being baked directly into the platforms enterprises already use. Intezer, an AI SOC platform for enterprises powered by ForensicAI™, now lets security teams build their own AI agents within the product, rather than relying only on vendor‑defined automation. At the same time, N‑able has added Shadow AI Visibility across its unified endpoint management tools N‑central and N‑sight and its security operations platform Adlumin, exposing previously hidden AI activity across endpoints and networks. Together, these moves show SOC work evolving from reactive manual investigation toward proactive, agent‑based threat detection automation and tighter endpoint security operations.
Intezer’s Custom Agents: Turning SOC Routines into Code-Free AI Workflows
The most important change is that custom security agents are no longer the domain of engineers; SOC users can design them in natural language. Intezer’s Custom Agents let security teams describe what they want done, define when it should run, and choose which connected tools the agent can use, all inside the platform. These agents sit on the same engine that already investigates 100 percent of alerts and escalates fewer than 2 percent for human review around the clock. In practice, teams are using agents for custom incident reports, recommendations on tuning detection rules based on triage verdicts, and proactive threat hunting across SIEM, EDR, and identity systems like CrowdStrike, SentinelOne, Splunk, Microsoft Sentinel, and Entra ID. Instead of scripting one‑off playbooks, analysts can convert repetitive chat‑based tasks into autonomous workflows. That turns the SOC from a queue of tickets into a factory of reusable, AI‑powered processes that cut mean time to response.
N‑able’s Shadow AI Visibility: Fixing the Blind Spot in Endpoint Security Operations
The other side of AI SOC automation is governance: you cannot secure what you cannot see. As AI adoption accelerates, employees are using AI apps, browser extensions, developer tools, APIs, and SaaS platforms outside formal approval processes, creating a new blind spot for endpoint security operations. A recent survey of 302 cybersecurity leaders showed that 69% suspect or have evidence that employees are using prohibited public generative AI. N‑able’s Shadow AI Visibility tackles this problem by identifying, classifying, and monitoring AI tool usage across endpoints and network activity without requiring extra agents or consoles. It inventories which AI tools are in use, by whom, on which devices, and with what approval status, and then exposes that data through integrated workflows in N‑central, N‑sight, and Adlumin. Instead of guessing where shadow AI lives, security teams can build evidence‑based AI governance and fold it into everyday endpoint security operations.
Why Now: SOC Overload, Shadow AI, and the MTTR Squeeze
The timing of these launches is not coincidental. Security teams can no longer rely on manual alert handling or isolated scripts to keep up with today’s threat volume and complexity. Intezer’s analysis of how customers used its AI chat found that more than a third of conversations were the same repetitive tasks requested again and again. Those patterns are a clear signal: much of SOC work is repetitive knowledge work that is ripe for threat detection automation. At the same time, unchecked shadow AI introduces new security, compliance, and operational risks because organizations lack visibility into which tools are used, by whom, and where. The result is pressure on mean time to response: teams must respond faster while managing new AI‑driven behaviors on endpoints. Custom agents that automate investigation and reporting, combined with visibility into unauthorized AI usage, are how SOCs square that circle—shortening response cycles without sacrificing oversight.
The New SOC Contract: Design Agents, Govern AI, Keep Humans in Charge
What these announcements signal is a new contract for enterprise security teams. Platforms like Intezer are saying: let autonomous agents do the security work while humans supervise outcomes. With Custom Agents available in beta and free during that period, teams can experiment with automating their unique routines—shift handoffs, documentation, tuning rules—without writing code. N‑able’s Shadow AI Visibility, already available in its endpoint and security operations products, provides the inventory and governance insights those same teams need to keep AI usage under control. The opinionated takeaway is clear: the future SOC is less about clicking through queues and more about designing, monitoring, and refining AI agents that embody the team’s expertise. Enterprise security leaders who embrace AI SOC automation and shadow AI visibility will cut MTTR and gain better control over endpoint security operations. Those who cling to manual workflows will find themselves outpaced by threats—and by their peers.
