Topic starter
22/09/2026 3:43 pm
TL;DR: Agentic AI breaks zero-trust assumptions by planning its own steps, retaining memory, and traversing multiple systems in a single workflow, according to NetFoundry. The control problem is no longer just perimeter defense or prompt scanning, but identity-first governance that binds every agent, endpoint, and MCP server to unique authorization and traceable access.
NHIMG editorial — based on content published by NetFoundry: The IT & Security Leader’s Guide to AI Governance
By the numbers:
- Only 44% of respondents see AI security decision-making power shifting toward platform and infrastructure teams rather than the executive suite.
- 70% of organisations grant AI systems more access than they would give a human employee performing the exact same job.
- Systems with least-privileged AI access had a 17% incident rate vs 76% for over-privileged systems.
Questions worth separating out
Q: How should security teams govern AI agents that move across multiple trust boundaries?
A: They need runtime controls that follow the agent rather than staying attached to one platform.
Q: Why do shared credentials become riskier when AI systems are in the workflow?
A: Shared credentials become riskier because AI systems can act at machine speed across multiple tools and sessions, while human governance still assumes slower, reviewable use.
Q: What breaks when AI agents are governed with static zero trust assumptions?
A: Static zero trust assumptions break when the agent can plan, remember, and reroute its own actions mid-session.
Practitioner guidance
- Implement separate identities for every agentic workflow Do not let AI agents share human or service-account credentials.
- Sequence governance as identity, then access, then data Start with who or what is connecting, define allowed reachability next, and only then apply classification, retention, or DLP controls across the workflow.
- Scope access at the agent instance level Bind permissions to the specific agent, endpoint, or MCP server rather than the host or platform alone, and deny new paths until they are explicitly authorised.
What's in the full article
NetFoundry's full guide covers the operational detail this post intentionally leaves for the source:
- A practical identity-first implementation path for AI agents, LLM endpoints, and MCP servers across hybrid and partner environments
- The specific architecture pattern for deny-by-default connectivity at the agent identity layer
- How the guide maps its approach to NIST AI RMF, NIST SP 800-207, and CISA zero trust guidance
- The case-study detail behind the July 2026 Hugging Face incident and what it exposed about attribution gaps
👉 Read NetFoundry's guide to AI governance for identity-first zero trust →
Agentic AI identity governance: what changes for zero trust teams?
Explore further
22/09/2026 3:43 pm
Identity-first governance is the only workable control plane for agentic AI. Agentic systems do not merely need more monitoring, because their runtime behaviour is dynamic and their reach spans multiple services in one task. Once an agent can plan and execute across cloud, SaaS, and partner infrastructure, zero trust has to start with identity binding, not after-the-fact review. The practitioner conclusion is that identity, access, and data must be sequenced, not treated as parallel workstreams.
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.
- Only 13% of organisations feel extremely prepared for the reality of agentic AI, which shows how quickly governance is lagging adoption.
A question worth separating out:
Q: Should organisations prioritise identity governance before expanding agentic AI?
A: Yes. Organisations should establish ownership, least privilege, monitoring, and revocation for machine identities before broadening agentic AI use. Without those controls, each new agent can multiply blast radius and create shadow access that is hard to unwind after an incident.
👉 Read our full editorial: Identity-first governance is the missing layer for agentic AI
