“Think about an AI agent that autonomously collects indicators of compromise [IOCs] from a number of risk feeds, correlates them with inner telemetry, enriches the information with context from OSINT and CTI [cyber threat intelligence] repositories, after which drafts a structured alert for an analyst.” As a substitute of ready for a SOC staff to pivot manually throughout completely different platforms, the agent executes the pivoting robotically, flags anomalies, and prepares a really useful response playbook.
Geenens believes his advised method, like many agentic AI use circumstances introduced right here, addresses two main cybersecurity ache factors: scale and pace. “Analysts are drowning in alerts and lack the time to attach dots throughout a number of sources,” he says. Agentic AI can successfully supplant repetitive, high-volume correlation duties. Extra necessary, it closes the hole between detection and mitigation, enabling analysts to concentrate on validation and technique relatively than operations. “In observe, this doesn’t substitute people, however amplifies experience whereas reducing by means of noise.”
4. Augmenting security expertise
One other huge downside in cybersecurity doesn’t concerned expertise — it’s the present expertise hole, and AI brokers present that almost all sensible reply, says Rahul Ramachandran, generative AI product administration director at Palo Alto Networks.
