I have been in information security for more than twenty years, and one of the conversations I have had more times than I can count goes something like this: the security team has spent eighteen months building out an identity and access management program. They have deployed a new IGA platform, cleaned up thousands of orphaned accounts, enforced multi-factor authentication across the enterprise, and automated the joiner-mover-leaver lifecycle. And then someone in the CFO’s office asks a simple question: what did we actually get for that investment? If your answer is a technical presentation about policy enforcement rules and connector configurations, you have already lost the room. If your answer is a blank stare because you never built a metrics framework to begin with, you have lost the budget cycle too. IAM is one of the highest-value security investments an organization can make. Identity is the new perimeter. Credential-based attacks are the dominant breach vector. And access...
AI agents are multiplying inside enterprise environments faster than identity governance programs can track them. They are being deployed by developers, operations teams, and business analysts — often without security involvement, without formal registration, and without the kind of access scoping discipline that any human identity would require. The service accounts they run under accumulate permissions. The credentials they use do not rotate. The ownership of those identities is tied to whoever built the agent, and when that person moves on, the agent keeps running with nobody accountable for what it can access or what it is doing. This is not a theoretical future risk. It is the current state in most organizations that have started adopting AI automation in any meaningful way. And it represents a significant gap in the IAM frameworks most security programs are built around — because those frameworks were designed for human identities, and AI agents are something fundamentally differ...