Microsoft 365 has become the backbone of enterprise collaboration, but SharePoint and OneDrive are often where sensitive data goes to be forgotten.

These platforms store decades of documents: contracts, financial models, HR exports, and client files. Many are broadly accessible via “anyone in the organization” links. Others are inherited or orphaned as roles change and users leave. File ownership is murky, labeling is inconsistent, and the audit trail is thin.

The challenge isn’t new, but AI is making it harder to ignore. Microsoft Copilot, enterprise search, and external apps can now surface old documents instantly through natural language prompts. These systems don’t understand business intent, they blindly follow entitlements.

Ask Copilot to summarize “performance review benchmarks,” and it may retrieve an internal HR folder that was broadly shared years ago. With no labeling or restriction, that content becomes a live data leak.

Even when organizations deploy Microsoft Purview’s DLP and sensitivity labels, operationalizing them at scale often proves difficult. Inconsistent labeling, fragmented policies across business units, and high false positive rates force many teams to keep the system in “monitor only” mode rather than blocking risky behavior.

Third-party tools like ChatGPT, Claude, and others can also be connected by end users via OAuth, often without visibility or governance. These apps can access document stores and, in some cases, train on them. Most teams don’t have controls in place to prevent this.

The risk is no longer a careless user. It’s the platform’s default behavior, amplified by AI.

To reduce exposure, you need a few foundational shifts:

• Continuous classification and labeling. Use AI-powered labeling to detect sensitivity and business context as files are created or updated, then apply Purview DLP policies to control access and sharing, ensuring labels are accurate to enforce at scale.
• Integration monitoring. Audit all apps and agents connected to Microsoft 365. Block unsanctioned tools, especially those with broad read access.
• Label enforcement. Use Purview DLP policies to restrict access to labeled content, but ensure the content is labeled correctly in the first place.
• Blast radius reduction. Find legacy link-shared and inherited files. Lock down wide-sharing defaults. Set expiration and access boundaries.
• Pre-deployment guardrails. Don’t roll out Copilot or enterprise AI integrations until your content layer is governed.

If a document lives in OneDrive with open org-wide access, assume that data inside it will be exposed by any AI tool with access.

What’s the oldest shared folder in your SharePoint environment? Do you know who still has access?

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