AI complementarity is the ability to work alongside AI rather than try to outmatch it directly. In cyber security, that means using automation for fast, repetitive tasks while humans provide judgment, context, and escalation. AI can summarize alerts, cluster logs, draft incident notes, or help analysts search large data sets; defenders then decide what is real, what is risky, and what needs immediate action.
This matters because attackers also use AI to scale phishing, generate malicious code, and speed up reconnaissance. A complementary approach helps security teams stay effective: analysts validate AI output, tune detections, review edge cases, and watch for model errors, prompt injection, and overreliance on automated decisions. The practical goal is not “AI versus people,” but a workflow where AI increases reach and speed while humans keep control of trust, strategy, and response.