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02/08/2026 11:25 am
TL;DR: AI-driven workflows are breaking four SASE assumptions, including perimeter relocation, traffic inspection as governance, and delivery unification as enforcement, according to Island. The real issue is that work now happens at the interaction layer, where network-only controls cannot reliably see intent, context, or local tool activity.
NHIMG editorial — based on content published by Island: Assumptions That No Longer Hold in SASE Network
By the numbers:
- 52% of remote-capable professionals work in hybrid arrangements, and another 26% work exclusively remote.
Questions worth separating out
Q: How should security teams govern AI workflows when network inspection is not enough?
A: They should move beyond traffic-only controls and govern the session where the work occurs.
Q: Why do SASE and backhauling models struggle with modern identity governance?
A: Because they assume the network path is the best place to understand risk, while many high-value actions now happen before or inside the application session.
Q: What do security teams get wrong about unified SASE enforcement?
A: They often assume one console means one decision model.
Practitioner guidance
- Map enforcement to the point of interaction Inventory where policy is actually decided for SaaS, AI tools, and delegated workflows, then compare that to where users and agents perform actions.
- Separate visibility from enforceability Review whether your inspection stack can prove what happened after a prompt, file upload, or tool call, not just that traffic reached a known endpoint.
- Reassess zero trust for AI-era workflows Use NIST SP 800-207 Zero Trust Architecture to test whether continuous verification still holds when identity, device state, and application context change mid-session.
What's in the full article
Island's full blog post covers the architectural detail this post intentionally leaves for the source:
- The step-by-step argument for why PoP-based backhauling no longer maps cleanly to AI-era work patterns.
- Specific examples of how prompt activity, local tool execution, and application-layer interactions evade network-only inspection.
- The article's comparison between delivery unification and enforcement unification in SASE architectures.
- Island's recommended direction for moving enforcement closer to the point of work.
👉 Read Island's analysis of why SASE backhauling assumptions are breaking in AI-era work →
SASE backhauling and AI workflows: where enforcement is failing?
Explore further
02/08/2026 12:42 pm
Point-of-interaction enforcement is now the governing model that matters. SASE-style backhauling can still contribute transport security, but it no longer answers the hardest question in AI-era operations: what is permitted inside the session after the connection is established. That creates a control gap between authentication and action, which is where modern abuse often lives. For identity programmes, this is the same shift seen in NHI governance and agentic AI control design. Practitioners should treat the interaction layer as a first-class enforcement surface, not a logging afterthought.
A question worth separating out:
Q: Who is accountable when AI or contractor activity bypasses network-level controls?
A: Accountability sits with the programme owner who defined the control boundary, not just the operator who ran the platform. If AI workflows, contractors, or third parties can act inside applications without session-level governance, then the architecture has failed to carry policy to the point of action. That is an identity and access design issue, not only a networking issue.
👉 Read our full editorial: SASE backhauling assumptions are breaking in AI-era work
