What Is AI Identity Lifecycle Management?

AI Identity Lifecycle Management involves discovering, inventorying, governing, monitoring, and retiring AI identities throughout their operational lifecycle. As organizations deploy more AI agents and autonomous systems, AI identities continuously evolve through new permissions, integrations, ownership changes, and data access, creating governance challenges that traditional identity management approaches fail to address. The process encompasses seven stages from initial discovery through retirement, helping organizations maintain visibility and accountability while mitigating risks from permission creep and abandoned systems.