Topic starter
06/09/2026 6:21 pm
TL;DR: Legacy IGA models built around users and roles do not fully govern service accounts, workloads and autonomous AI agents, SafePaaS says. Identity governance now needs ownership, runtime context and business-aware controls that follow non-human activity into actual transactions.
Editorial analysis by NHI Mgmt Group, based on content published by SafePaaS: “SafePaaS Named a Representative Vendor in the 2026 Gartner® Market Guide for Identity Governance and Administration”.
Key questions
Q: Why do AI agents change the way IAM and governance teams think about access?
A: AI agents change access governance because the relevant privilege is not just the account they hold, but the task, context, and tool chain active during execution.
Q: How should security teams include non-human identities in IGA?
A: Treat service accounts, tokens, and application identities as governed assets with owners, purpose, expiry, and review cadence.
Q: What breaks when identity governance is built without strong role foundations?
A: Reviews become repetitive exceptions management, because certifiers have no stable baseline for what access should exist.
Practitioner guidance
- Inventory all non-human identity sources Build a complete register of service accounts, workloads, application identities and autonomous AI agents across cloud, SaaS and on-premises systems.
- Attach business context to entitlements Tag each access relationship with the business process, transaction type or control it supports so reviews can judge whether access is still appropriate in context.
- Move governance closer to runtime activity Use controls that can evaluate actions when they occur, not only during periodic access recertification.
Bottom line: Legacy IGA models built around users and roles do not fully govern an enterprise where service accounts, workloads and AI agents are active participants.
Glossary terms: Identity Governance and Administration (IGA), Non-Human Identity (NHI), Federated Identity, Runtime Governance
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This topic was modified 2 days ago by NHI Mgmt Group
06/09/2026 6:21 pm
Legacy IGA is now a partial control, not a complete governance model: systems designed mainly for users and roles cannot fully govern environments where service accounts, workloads and autonomous AI agents act alongside humans. The article reflects a broader market truth: identity scope has outgrown the original architecture of access administration. Practitioners should treat coverage gaps across non-human identities as a structural governance deficit, not a tuning issue.
A few things that frame the scale:
- 19% of organisations give AI systems dramatically more access than human employees, nearly one in five granting unrestricted privilege, according to the 2026 Infrastructure Identity Survey.
- Systems with least-privileged AI access had a 17% incident rate vs 76% for over-privileged systems. Organisations failing to scope AI access properly are 4.5x more likely to experience a security incident, according to the 2026 Infrastructure Identity Survey.
A question worth separating out:
Q: What should organisations do when AI outputs can influence transactions or advice?
A: Treat the model as part of a delegated business workflow and apply scoped permissions, logging, and human approval before any customer-impacting action. The practical standard is not whether the model sounds safe, but whether it is technically prevented from crossing the action boundary.
👉 Read our full editorial: Gartner recognition spotlights AI-aware identity governance gaps