Security teams are under pressure to respond faster as attacks become more automated and less predictable. Alert queues, manual triage, and static rules struggle to keep up, especially in busy SOCs and multi-tenant MDR environments.
AgileBlue has introduced agentic AI agents designed to operate as active SOC teammates.
These agentic AI agents are designed to assess activity on their own, decide whether it is a real threat, and take action when required. The goal is to shift security operations away from slow, analysis-heavy workflows toward faster response, where decisions and remediation happen with fewer handoffs and delays.
Moving Beyond “Agent-Washing”
As more vendors describe their platforms as agentic or autonomous, the term itself has become diluted. AgileBlue argues the difference is not branding but architecture.
Tony Pietrocola, President of AgileBlue, told MSSP Alert, “The overwhelming majority of vendors are not truly AI-native. The industry is currently ‘agent-washing’ basic automation, but the distinction is architectural by nature,” an AgileBlue spokesperson told MSSP Alert. “Co-pilots and assistants are essentially waiting for human instructions to retrieve and display data. Our agentic platform operates as an autonomous teammate.”
According to Pietrocola, this autonomy is grounded in reasoning, not scripted automation. “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,” said Pietrocola.
From Alerts to Action Inside the SOC
Unlike tools that stop at alert enrichment or recommendations, AgileBlue’s agents are designed to carry incidents through investigation and remediation. When a threat is confirmed, the agents can initiate response actions directly, without waiting for analyst approval.
This matters as attackers increasingly use automation to scale campaigns. Security platforms that depend on human handoffs at every stage risk falling behind. Autonomous decision-making compresses response timelines and reduces the operational drag caused by constant context switching.
What This Changes for MSSPs
For MSSPs running multi-tenant SOCs, agentic AI is closely tied to analyst workload and SLA performance. AgileBlue says early results show a meaningful impact.
“First, we have seen incredible results. A reduction of close to 72% of human work on false positives and a nearly 49% reduction in work on malicious cases,” Pietrocola said. “This is serious efficiency leading to faster, more accurate work, and this is just the beginning.”
The company expects those gains to continue. “We expect those numbers to increase significantly throughout 2026,” Pietrocola added.
The agents are designed to handle common investigation and response tasks end to end. “These agents can make decision and response actions to isolate machines, disable 365/GSuite and AD accounts, stop a program or event from executing, block IPs, delete an email and many other typical response actions,” Pietrocola said.
AgileBlue is positioning its agentic AI agents as support for human analysts, not replacements. Analysts retain visibility and control, while agents handle repetitive investigation and response work that often leads to fatigue and inconsistency.
By embedding autonomous decision-making directly into security operations, AgileBlue is aiming to help security teams and MSSPs scale more predictably, protect SLAs, and keep pace with increasingly automated threats without continually adding headcount.
