Notifications
Clear all
Topic starter
07/06/2026 8:38 pm
TL;DR: As companies add AI agents, the identity footprint can multiply quickly, with one example showing ten agents calling one hundred tools can create 10,000 credentials to manage, according to ConductorOne. The governance challenge is no longer just human IAM. It is consistent authentication, authorization, monitoring, and review across humans, service accounts, and agent-driven tool chains.
NHIMG editorial — based on content published by ConductorOne: Human vs. Non-Human Identities Explained
Questions worth separating out
Q: How should security teams govern non-human identities alongside human accounts?
A: Treat non-human identities as first-class subjects in IAM, not as exceptions handled by platform teams.
Q: Why do AI agents make identity governance harder?
A: AI agents make governance harder because they can hold credentials, call tools, and trigger actions across multiple systems, which multiplies the number of identities and permissions involved in one workflow.
Q: What breaks when service accounts are left out of lifecycle governance?
A: Service accounts that are not owned, reviewed, or removed on time tend to accumulate stale permissions and remain active after the workload they support has changed.
Practitioner guidance
- Inventory every non-human identity path Build a complete register of service accounts, API keys, tokens, certificates, and AI agent credentials, including the tools and downstream systems each one can reach.
- Map delegated tool chains end to end Trace each AI agent from the first data source it touches to the final system action it can trigger, then document every identity involved in the chain.
- Extend lifecycle controls to machine identities Apply joiner-mover-leaver style governance to service accounts and automation identities so credentials are created with an owner, reviewed on schedule, and removed when the workload or integration ends.
What's in the full article
ConductorOne's full blog covers the practical identity patterns this post intentionally leaves at a higher level:
- Examples of how service accounts, APIs, and agent tool calls are grouped into identity workflows
- The article's own framing of AI agent identity patterns inside modern infrastructure
- The specific ways ConductorOne recommends teams think about governance and review across human and non-human identities
👉 Read ConductorOne's explanation of human and non-human identities →
Non-human identities and AI agents: what IAM teams need now?
Explore further
08/06/2026 8:16 am
Non-human identity governance is now an enterprise identity problem, not a niche security subdomain. The article is right to frame NHIs as part of the core identity estate rather than as a side concern for platform teams. Service accounts, API keys, tokens, and AI agents all create access paths that can outlive human awareness. The governance consequence is straightforward: IAM programmes that still treat NHI as an edge case will miss the bulk of machine access activity.
A few things that frame the scale:
- 91.6% of secrets remain valid five days after the targeted organisation is notified, showing a critical gap in remediation procedures, according to the Ultimate Guide to NHIs.
- Only 20% have formal processes for offboarding and revoking API keys, and even fewer have procedures for rotating them.
A question worth separating out:
Q: Should organisations treat agent access reviews the same as human access reviews?
A: No. Human reviews focus on role, business need, and employment status, while agent reviews must also cover tool scope, credential inheritance, and downstream action paths. The review object is not just the agent itself but the full execution chain it can initiate. That distinction matters because agent behaviour can change faster than a standard recertification cadence can capture.
👉 Read our full editorial: Human vs. non-human identities: why governance now spans agents
