Enterprises should model AI agent identity in two layers. A "Stable Agent Principle" acts like a permanent user account for governance, while a "Temporal Runtime Identity" acts like a temporary session for specific actions. This prevents overwhelming identity systems while ensuring full auditability and accountability for every agent action.
Don't let fears of "directory overload" prevent you from creating attributable AI agents. The governance requirement to trace every agent action is non-negotiable. The solution is not infinite directory entries, but a system of stable identities linked to temporal records for a full audit trail. The technical implementation should not compromise the governance requirement.
Adopting a comprehensive AI identity model can be done in phases. First, register agents as governable actors with stable identities and roles. Later, add runtime instance linkage and detailed context lineage. This incremental path provides immediate and significant governance gains without requiring a complete overhaul of identity systems from day one.