Task allocation is the division of work between humans and machines. In AI-enabled security systems, it decides what the system can automate, what it can assist, and what still needs a person’s judgment. Common examples include alert triage, malware classification, spam filtering, log analysis, and account-lockout decisions.
This matters because security outcomes depend on where automation stops. If a model handles repetitive checks, defenders gain speed and scale. If it is given high-impact decisions such as blocking users, approving access, or escalating incidents, errors can cause outages, missed threats, or unfair denial of service. Attackers also study these boundaries: they may overwhelm automated queues, trigger false positives, or use AI to automate reconnaissance and phishing while humans handle adaptation. Good task allocation keeps critical actions reviewable, limits the blast radius of mistakes, and preserves human oversight where context, intent, and recovery matter most.