technology
AI Agents in Cybersecurity Add Complexity Instead of Reducing Workload
Siloed AI agents in security tools perform isolated tasks but cannot share context or coordinate actions. Enterprises are adopting agentic systems that orchestrate multiple agents toward unified security outcomes.
May 21, 1:24 PM·1m read1 source
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AI agents deployed in cybersecurity tools typically handle single tasks such as scanning for indicators of compromise or generating detection queries. These agents operate independently and cannot exchange information with other agents, limiting their ability to address full attack lifecycles.
Security teams must manually connect outputs from multiple disconnected agents. This coordination burden creates delays, increases staffing costs, and keeps analysts focused on alert triage rather than proactive threat identification.
An agentic system uses an orchestrator to direct specialized agents that share memory and business context. Agents are organized into personas mapped to roles such as Detection Engineer or Threat Hunter and can access more than 200 skills and 400 AI tools.
Users can direct these systems through natural language requests. The systems then execute complex workflows autonomously, such as planning hunts, querying telemetry, detecting anomalies, and generating reports for human review.
Global convenience store operator Circle K deployed an agentic platform across IT and OT environments in more than 25 countries. The company consolidated security operations onto a single platform after frequent acquisitions introduced new legacy systems.
Mean time to contain threats fell from 24 hours to five minutes following the deployment. The platform continues to operate across retail point-of-sale systems and fuel terminal infrastructure worldwide.
