Topic starter
06/09/2026 6:21 pm
TL;DR: AI agents, service accounts and workloads are colliding with legacy IGA models built mainly for users and roles, while SafePaaS was named a Representative Vendor in Gartner’s 2026 Market Guide for Identity Governance and Administration. The real issue is not recognition itself, but that access governance now has to follow identities into runtime activity, ownership and business context.
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: 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.
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.
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.
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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