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09/06/2026 11:40 pm
TL;DR: Microsoft Copilot readiness depends on discovering sensitive data, classifying it, and removing excessive access across Microsoft 365 and hybrid environments, according to Netwrix. The core issue is not Copilot itself but the permission debt and data visibility gaps that existing IAM and PAM controls leave behind.
NHIMG editorial — here’s why we think this discussion matters
By the numbers:
- Only 44% of organisations have implemented any policies to manage their AI agents, despite 92% agreeing that governing AI agents is critical to enterprise security.
Questions worth separating out
Q: How should security teams prepare Microsoft 365 data for Copilot access?
A: Security teams should start with discovery, then classification, then privilege cleanup.
Q: Why does excessive permissions matter more when AI assistants are enabled?
A: AI assistants can search and summarise content across many locations quickly, so old permission mistakes become faster exposure paths.
Practitioner guidance
- Inventory sensitive data across collaboration and on-prem systems Map where regulated, confidential, and business-critical content resides in SharePoint, Teams, OneDrive, and connected file stores before enabling broad Copilot use.
- Classify content before expanding AI access Apply sensitivity labels to the repositories and file types that Copilot will search so downstream DLP policies have a reliable policy signal.
- Recertify inherited and shared permissions Target nested groups, stale sharing links, and workspace permissions that create permission debt and remove access that no longer matches current job need.
What to expect at the briefing
Netwrix's full webinar covers the operational detail this post intentionally leaves for the source:
- Automatic discovery and classification workflows for Microsoft 365 and on-prem content that need implementation detail.
- Practical use of Microsoft Purview sensitivity labels alongside DLP policy design and enforcement tuning.
- Permission remediation approaches for excessive access across SharePoint, Teams, and OneDrive.
- PAM and access governance considerations for reducing standing access before Copilot rollout.
👉 Watch Netwrix's on-demand webinar on Microsoft Copilot readiness and data access control →
Copilot readiness and permission debt: what IAM teams need to know?
Explore further
10/06/2026 2:05 am
Copilot readiness is a data access governance problem before it is an AI problem. Organisations are trying to control summarisation, but the real risk sits in the underlying permission structure that decides what Copilot can see. If sensitive content is still scattered across collaboration platforms with weak classification and uneven entitlement hygiene, the AI layer simply makes existing exposure easier to reach. Practitioners should treat readiness as a governance cleanup exercise, not a feature rollout.
A few things that frame the scale:
- 67% of organisations still rely heavily on static credentials despite the risks they pose to agentic AI deployments, according to The 2026 Infrastructure Identity Survey.
- Only 44% of organisations have implemented any policies to manage their AI agents, even though 92% agree that governing AI agents is critical to enterprise security.
A question worth separating out:
Q: Should organisations prioritise data classification or permission cleanup first?
A: In practice, they should do both in sequence: classify the highest-risk data first, then use that map to remove excessive access. Classification without permission cleanup leaves exposure intact, while cleanup without classification misses where the real risk sits. The right order is to identify critical data, then narrow who can reach it.
👉 Read our full editorial: Microsoft Copilot readiness exposes permission debt in data access
