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15/05/2026 7:34 pm
TL;DR: AI agents can chain decisions, delegate across systems, and stay within existing permissions while still acting beyond intended scope, according to Omada Identity and the Brave Comet demonstration it cites. The governance gap is now about proving authorised behaviour, not just limiting access.
NHIMG editorial — based on content published by Omada Identity: Governing AI Agents, What Changes When Identities Make Decisions
Questions worth separating out
Q: How should security teams govern AI agents that can make decisions on their own?
A: Security teams should govern AI agents by assigning each one a documented authority scope, an accountable owner, and explicit limits on tools, data, and actions.
Q: Why do AI agents create more risk than ordinary service accounts?
A: AI agents create more risk because they can interpret context, chain actions, and delegate through other identities instead of just executing fixed instructions.
Q: What is the difference between access review and agent governance?
A: Access review checks whether an identity still needs permissions.
Practitioner guidance
- Define authority before deployment Document each agent’s business purpose, human sponsor, accountable owner, allowed tools, permitted data domains, and prohibited actions before production rollout.
- Map delegation paths end to end Trace how an agent can combine other agents, service accounts, and tool calls to complete a task, then review the full chain as one authorization decision.
- Monitor runtime drift continuously Compare observed agent behaviour against approved scope using cloud logs, SaaS events, IAM activity, and SIEM telemetry, then constrain or suspend when drift appears.
With 67% of organisations still relying heavily on static credentials, the control problem is clearly still anchored in old IAM assumptions, according to the 2026 Infrastructure Identity Survey?
👉 Read Omada Identity's analysis of governing AI agents and decision-making identities →
Explore further
15/05/2026 7:35 pm
Defined authority is the minimum viable control for AI agents. If an agent cannot be tied to a declared purpose, owner, scope, and review cadence, governance becomes forensic guessing after the fact. Identity programs have spent years learning that ownership and lifecycle are not optional for NHIs, and agents raise the stakes by adding decision-making to the same control problem. Practitioners should require authority scopes before deployment.
A few things that frame the scale:
- 70% of organisations grant AI systems more access than they would give a human employee performing the exact same job, according to the 2026 Infrastructure Identity Survey.
- 52% of respondents say AI security decision-making power is shifting toward platform and infrastructure teams, which shows governance ownership is moving closer to operations.
A question worth separating out:
Q: When should organisations add continuous controls for AI agents?
A: Organisations should add continuous controls as soon as an agent can select tools, act across systems, or delegate to other non-human identities. Those capabilities create runtime drift and delegation risk that periodic certification cannot see fast enough. Continuous oversight becomes necessary once the agent can change its own action path.
👉 Read our full editorial: AI agent governance needs defined authority and runtime evidence
