SCWorld.com reported that “AI agents with system access create identity risks that traditional governance frameworks miss. These automated actors authenticate with privileged credentials, access sensitive data, and modify systems without human intervention. When organizations extend user access management to AI agents without adapting the controls, they create persistent privileged access that can outlive business justification and remain invisible to quarterly access reviews.” The May 29, 2026 article entitled ” How to Build an AI Governance Framework for Identity” (https://www.scworld.com/program-guide/how-to-build-an-ai-governance-framework-for-identity) included these comments:
The operational consequence: AI agents accumulate excessive permissions that survive project endings, team changes, and evolving business requirements. A task automation agent deployed for a three-month data migration project can retain database access indefinitely if the deprovisioning process assumes human departure triggers.
Governance frameworks that treat AI agents as a distinct identity category with purpose-specific lifecycle controls change this outcome.
Most identity programs apply user-centric assumptions to non-human actors. Access certification processes ask managers to review AI agent permissions they didn’t request and don’t understand. Quarterly reviews present lists of service accounts without business context about the AI workloads they support. Risk escalation procedures route AI agent access violations to human supervisors who lack technical context to assess impact.
The downstream business risk is uncontrolled privileged access expansion and compliance gaps during audits.
What do you think?