Topic starter
26/08/2026 11:51 am
TL;DR: AI agents now operate with broad, long-lived access across code, data, and business systems, and Cakewalk argues that traditional IAM, NHI management, and observability do not provide action-time authorization. The core gap is that agent behaviour is emergent at runtime, so access decided at setup time leaves governance blind when it matters most.
Editorial analysis by NHI Mgmt Group, based on content published by Cakewalk: “The New Frontier in Identity Security: AI Agent Access”.
Key questions
Q: What breaks when AI agents are governed like ordinary service principals?
A: The main failure is that ordinary service-principal governance assumes a stable workload with predictable lifecycle and entitlement patterns.
Q: Why do AI agents increase identity risk even when the login succeeds?
A: A successful login only proves that the agent reached the system.
Q: How should security teams set access boundaries for AI agents?
A: Security teams should define agent boundaries around data sources, tools, and allowed actions before any production rollout.
Practitioner guidance
- Implement per-action authorisation for agents Evaluate every tool call, API request and database query against policy before execution, with allow, deny or human-review outcomes based on action type and data sensitivity.
- Separate agent permissions from human permissions Map which human entitlements can be delegated and which must be removed or narrowed for the agent, so an agent never inherits the full authority of the person who triggered it.
- Inventory unsanctioned and unmanaged agents Build an inventory of active agents, the credentials they hold and the systems they can reach, then identify sessions operating without approved ownership or policy coverage.
Bottom line: AI agents now expose a governance gap that traditional IAM was not built to close, because runtime decisions cannot be safely managed with setup-time permissions alone.
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26/08/2026 11:51 am
Action-time authorisation is the missing control plane for AI agents: Cakewalk’s core point is that setup-time access decisions were designed for actors whose next step is knowable in advance. Agents discover their own paths, so the security decision must move to the moment of execution. That is the governance shift practitioners should now treat as non-optional.
A few things that frame the scale:
- AI-related credential leaks surged 81.5% year-over-year in 2025, with the surrounding AI infrastructure leaking 5x faster than core LLM providers, according to the State of Secrets Sprawl 2026.
- 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.
A question worth separating out:
Q: Should organisations treat AI agents like human users in IAM?
A: No. Human IAM assumes a person logs in, works within a session, and can be reviewed later as a stable identity holder. Agents can act at machine speed, across multiple systems, and with changing runtime context, so they need identity governance built around execution and delegation rather than human authentication patterns.
👉 Read our full editorial: AI agent access is breaking traditional identity security models