The concept of “agentic AI” refers to autonomous systems that go beyond traditional AI functions by not just analysing or generating, but reasoning, planning and acting on their own toward defined goals. In cybersecurity, this shift is becoming especially relevant: instead of awaiting human commands, these agents can autonomously detect threats, prioritise vulnerabilities, execute response actions and adapt their behaviour over time.
On the defensive side, agentic AI promises major advantages. For instance, it can relieve alert-fatigue in Security Operations Centers (SOCs) by autonomously investigating routine incidents, escalating only the ones needing human review. It can also enable continuous vulnerability scanning and intelligent prioritisation, allowing organisations to scale security efforts without simply adding more headcount.
However, these benefits come bundled with important risks. Autonomous agents introduce new attack surfaces: examples include prompt injection, where a malicious actor manipulates the agent’s inputs; jail-breaking, where the agent is tricked into performing actions outside rule-sets; and data-access issues, where agents inadvertently expose or misuse sensitive information. Effective governance and human-in-the-loop oversight are critical safeguards.
In conclusion, agentic AI marks a pivotal evolution in cybersecurity — a transition from human-driven tools to machine-driven defence and offence. Organisations that adopt it stand to gain significant edge, but must concurrently invest in trust, control and transparency. The future will likely depend not just on deploying smart agents, but on how we govern them and integrate them responsibly into broader security ecosystems.
