Agentic AI in the SOC: From Alert Queues to Real Action
Security teams are burning time on alert queues, manual triage, and static rules while attackers move faster with automation. That gap is where incidents slip through. Operations leaders need workflows that make decisions and act, not just analyze.
AgileBlue is pushing agentic AI agents as active SOC teammates. These agents assess activity on their own, decide if it's a real threat, and take action when it is. The point is simple: fewer handoffs, less drag, faster response.
Moving Beyond "Agent-Washing"
Plenty of tools call themselves agentic or autonomous. Most are assistants waiting for instructions. The difference here is architecture, not branding. As AgileBlue positions it: co-pilots fetch and display; agents reason and execute.
Tony Pietrocola, President of AgileBlue, put it this way: "The overwhelming majority of vendors are not truly AI-native... Co-pilots and assistants are essentially waiting for human instructions to retrieve and display data. Our agentic platform operates as an autonomous teammate."
That autonomy is based on reasoning, not scripts. "Our agentic agent has moved beyond simple 'if-then' triage to a reasoning-based workflow where the AI can investigate, decision and respond with or without the assistance of humans, with a high degree of confidence," Pietrocola said.
From Alerts to Action Inside the SOC
Most tools enrich alerts and provide recommendations. These agents carry an incident from investigation to remediation. When the threat is confirmed, they initiate response without waiting for analyst approval.
That shift matters. Attackers scale their campaigns with automation. If every step in your SOC requires a human handoff, you're already behind. Autonomous decisions compress timelines and cut the context switching that kills throughput.
What This Changes for MSSPs and Ops Leaders
For multi-tenant SOCs, agentic AI ties directly to workload, capacity, and SLAs. AgileBlue reports early gains: "A reduction of close to 72% of human work on false positives and a nearly 49% reduction in work on malicious cases," Pietrocola said. They expect those numbers to rise through 2026.
Crucially, these agents don't replace analysts-they support them. Analysts keep visibility and control. Agents handle repetitive investigation and response, reducing fatigue and improving consistency across tenants.
What the Agents Can Do Today
- Isolate machines
- Disable Microsoft 365/Google Workspace and Active Directory accounts
- Stop a program or event from executing
- Block IPs
- Delete malicious emails
The goal is predictable scale without piling on headcount. Cleaner queues, faster decisions, tighter SLAs.
Practical Implementation Notes
- Define guardrails: Set approval thresholds by risk level and tenant sensitivity.
- Start with playbooks that create the most toil: phishing, malware on endpoints, suspicious auth.
- Measure what matters: MTTR, false-positive rate, analyst touch per incident, and SLA adherence.
- Keep audit trails: Every autonomous action should be explainable and reviewable.
- Segment by tenant: Enforce data boundaries and response policies per client.
- Train the team: Teach analysts how to supervise, tune, and escalate from agent output.
Why This Matters Now
Attackers use automation to scale. If your SOC's default mode is slow, analysis-heavy workflow, you'll see more backlog, more fatigue, and more missed windows to contain threats. Agentic execution closes that gap.
The future of operations is fewer manual steps and more confident, explainable automation-paired with humans who set guardrails and focus on the hard calls.
Further Reading
- NIST SP 800-61: Computer Security Incident Handling Guide
- MITRE ATT&CK: Adversary tactics and techniques
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