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22/07/2026 4:38 pm
TL;DR: Legacy IAM assumes the thing logging in is a person, but AI agents make hundreds of API calls per minute, spawn sub-agents, and change scope mid-task, according to Pomerium. That breaks human-paced review, static role mapping, and owner-based accountability, making identity-first enforcement and continuous verification the practical baseline.
NHIMG editorial — based on content published by Pomerium: Your IAM Was Built for People. Your Biggest Identity Problem Isn't People Anymore
By the numbers:
- Machine identities outnumber human ones by anywhere from 80 to 1 to more than 100 to 1 in the modern enterprise.
- Only 18% expressing high confidence that their existing identity systems can effectively manage agent identities.
- 71% of enterprises experienced an identity-related breach in 2025.
Questions worth separating out
Q: How should security teams govern AI agents that can change actions at runtime?
A: Security teams should govern runtime AI by correlating identity, data, and intent before trusting an action path.
Q: Why do AI agents break traditional IAM assumptions?
A: AI agents break IAM assumptions because they do not behave like predictable users.
Q: What do security teams get wrong about non-human identity governance?
A: They often treat service accounts and tokens as static technical assets instead of governed identities with owners, lifecycle events, and offboarding requirements.
Practitioner guidance
- Map where human IAM assumptions no longer fit Identify workflows where the actor is an AI agent or other non-human identity, then mark every control that assumes a manager-approved role, a stable session, or human-paced approval.
- Move authorisation to the request layer Place policy enforcement in an identity-aware proxy or equivalent control that checks every request outside the agent, so the actor cannot self-authorise once delegated scope begins to drift.
- Eliminate shared machine credentials Replace shared service accounts and long-lived API keys with distinct identities and short-lived credentials for each workload or agent, so accountability does not collapse across multiple actors.
What's in the full article
Pomerium's full blog post covers the operational detail this post intentionally leaves for the source:
- How its identity-aware proxy enforces per-request policy for agent workloads in front of applications and services
- How short-lived credentials and identity propagation are handled across multi-hop service calls
- How the infrastructure-level audit log preserves attribution for agent actions without relying on the agent itself
- How the zero trust pattern is applied to autonomous AI without reworking the workload architecture
👉 Read Pomerium's analysis of why IAM built for people fails for AI agents →
Agentic AI identity and IAM assumptions are colliding fast?
Explore further
22/07/2026 4:42 pm
People-first IAM is the wrong operating model once the subject is an agent. Human identity programmes assume a person, a manager, and a session that lasts long enough to review. That assumption is structurally mismatched to agentic AI identity, where runtime decisions and delegation can change faster than governance can observe. The implication is that identity governance must stop treating all principals as if they behave like employees.
A few things that frame the scale:
- 97% of NHIs carry excessive privileges, increasing unauthorised access and broadening the attack surface, according to Ultimate Guide to NHIs.
- Only 5.7% of organisations have full visibility into their service accounts, according to Ultimate Guide to NHIs.
A question worth separating out:
Q: Who is accountable when an AI agent uses delegated access incorrectly?
A: Accountability should follow the delegated authority chain, not stop at the agent label. The relevant owners are the teams responsible for the human identity, the service identity, the workflow, and the policy that allowed the action path. If those responsibilities are not explicit, incident review will be incomplete and remediation will focus on the wrong layer.
👉 Read our full editorial: Why agentic AI breaks people-first IAM assumptions
