Keeper Security’s introduction of structured PAM approval workflows that govern both human and AI agent access represents a fundamental shift in how organisations approach privileged access management. The new KeeperPAM workflows explicitly recognise that human administrators and AI agents are not interchangeable actors — they have different authentication requirements, different access patterns, and different risk profiles.
The problem KeeperPAM’s new workflows address is one that most organisations have not yet fully recognised: PAM platforms designed for human users make poor decisions about machine identity access. A human administrator requesting privileged access should be challenged with context-aware authentication — who are you, where are you, is this access expected? An AI agent requesting privileged access should be challenged differently — is this agent supposed to exist, does it have a valid provisioning record, is this action within its authorised scope?
Structured governance for both humans and agents requires different approval workflows. For humans, approval might be based on role-based access control (RBAC), resource criticality, and policy governance. For agents, approval might be based on automated provisioning records, infrastructure-as-code declarations, and expected access patterns. KeeperPAM’s approach is to recognise these differences explicitly and build approval workflows that account for them.
The business and security implications are significant. As organisations deploy more AI agents, the traditional PAM approval model breaks down. Agents are provisioned dynamically, their access requirements are often deterministic (they always need the same access), and manual approval processes create bottlenecks. Structured workflows that can handle both human and agent access patterns enable organisations to scale agent deployment without losing visibility or control.
For PAM practitioners, the takeaway is that AI-era PAM requires differentiated governance. The approval workflow that works for human privileged users is not appropriate for machine identity access. Platforms that recognise this distinction and build separate governance paths for humans and agents will be better positioned to serve organisations navigating the rapid growth of autonomous AI systems.