The shift toward autonomous AI agents has created a critical "Identity Gap" where legacy IAM and OAuth 2.0/OIDC protocols fail to manage the non-deterministic agency of Non-Human Identities (NHIs). This gap enables "invisible administration," where agents accrue permissions beyond their intended scope without direct attribution to a human principal. The lack of identity anchoring leads to systemic risks, including unauthorized privilege escalation, identity spoofing, and accountability voids during agentic misbehavior. Remediation requires transitioning to intent-based authorization via Policy-as-Code (PaC) and implementing immutable agentic provenance to link every autonomous action back to a verifiable human owner.

• Strategic Context: The Identity Gap

  • Transition from human-centric to agent-centric computing rendering traditional service accounts obsolete.
  • Failure of existing IAM models to account for the autonomy and non-deterministic nature of AI agents.
  • Necessity of treating agents as a distinct class of Non-Human Identities (NHIs) with traceable links to human principals.

• Technical Limitations of Legacy Frameworks

  • OAuth 2.0 and OIDC limitations regarding long-lived, high-agency delegation and session management.
  • Inability of standard protocols to track multi-step, autonomous decision chains across distributed environments.
  • Risk of "Invisible Administrators" who bypass governance by operating within delegated scopes without oversight.

• High-Impact Risk Vectors

  • Privilege escalation occurring through unauthorized delegation or agent-to-agent permission transfers.
  • Identity spoofing where autonomous entities assume high-privileged personas to execute restricted actions.
  • Operational accountability voids resulting in legal and technical ambiguity when agents misbehave in production.

• Proposed Defense Architectures

  • Implementation of Policy-as-Code (PaC) to enforce fine-grained, intent-based authorization and restrict agentic drift.
  • Deployment of agentic provenance systems to create immutable, machine-readable logs of all decision-making chains.
  • Integration of dynamic governance frameworks capable of real-time risk scoring and automated credential revocation.

• Industry Impact and Compliance Outlook

  • Shift toward verifiable, machine-readable identities to satisfy audit requirements for autonomous systems.
  • Emergence of new legal frameworks to address the liability of autonomous entities acting on behalf of organizations.
  • Integration of NHI management into the core enterprise security posture to prevent shadow AI deployments.