How AI in Microsoft Purview Is Changing Content Classification — and How We Deploy It

Most businesses have more sensitive data than they realise — scattered across SharePoint libraries, OneDrive folders, Exchange mailboxes, and Teams channels. Contracts, financial records, health information, client PII — it’s everywhere, and manually labelling it is a losing battle.

Microsoft Purview has spent years building tools to solve this. But the recent wave of AI-powered trainable classifiers and auto-labelling enhancements has fundamentally shifted what’s possible. Classification that once took months of manual policy-writing can now be bootstrapped in days.

Here’s what’s changed, why it matters, and how we help our clients deploy it.

What Are Trainable Classifiers?

Traditional data-loss prevention relies on pattern matching — regular expressions that look for credit card numbers, IRD numbers, or passport formats. That works for structured data, but it completely misses contextual content like legal privilege documents, strategic business plans, or signed contracts.

Trainable classifiers take a different approach. Instead of searching for patterns, they learn to recognise what a document is by analysing hundreds of examples. You feed the classifier sample documents that definitely belong to a category and samples that definitely don’t, and the model learns the difference.

Microsoft provides dozens of pre-trained classifiers ready to use out of the box:

• Legal documents — attorney–client privilege, statements of work, closing sets
• Financial information — invoices, quarterly results, investment documents
• Strategic business documents — press releases, M&A materials, IP and patents
• HR content — employment agreements, disciplinary records, benefits enrolments
• Healthcare data — clinical reports, patient records

These classifiers work immediately — no training data required. Just point them at your content and they start identifying matches across SharePoint, OneDrive, Exchange, and Teams.

What’s New: AI-Driven Enhancements

Microsoft has been rapidly expanding Purview’s AI capabilities, particularly around Copilot readiness:

1. Auto-Labelling at Scale

Sensitivity labels can now be automatically applied based on trainable classifier outputs — not just pattern matches. This means a document identified as “attorney–client privilege” by the classifier can be instantly labelled, encrypted, and access-restricted without anyone touching it.

Auto-labelling now processes content across:

• SharePoint Online and OneDrive for Business
• Exchange Online (emails and calendar events)
• Microsoft Teams messages and files
• Loop components and pages

2. DSPM for AI — Data Security Posture Management

The new Data Security Posture Management for AI dashboard gives organisations a single pane of glass to:

• Discover what sensitive data exists and where it’s exposed
• Assess oversharing risks before enabling Copilot and AI agents
• Apply one-click policies to lock down sensitive content
• Monitor how AI apps interact with labelled and encrypted data

This is critical for any business rolling out Microsoft 365 Copilot — without proper classification, Copilot can surface sensitive documents to users who shouldn’t see them.

3. Custom Classifiers for Your Industry

While the pre-trained classifiers cover common categories, custom trainable classifiers let you build models tailored to your organisation. For example:

• A law firm can train a classifier to identify file notes, cost agreements, or trust account records
• A healthcare provider can classify clinical notes vs. administrative correspondence
• A manufacturer can detect proprietary design documents or supplier agreements

You provide the training samples, Purview trains the model, and it begins classifying content across your entire tenant.

4. Sensitivity Labels and Copilot Integration

When AI apps — including Microsoft 365 Copilot, Security Copilot, and Copilot Studio — retrieve data, Purview enforces sensitivity labels automatically:

• Users must have EXTRACT and VIEW rights for encrypted content to be returned
• The sensitivity label is displayed in context within Word, Excel, PowerPoint, and Outlook
• Labels are inherited by new content that Copilot generates from labelled sources

This means your labels follow your data everywhere — even into AI-generated summaries and drafts.

Why This Matters for Your Business

Without proper classification, businesses face three escalating risks:

1. Regulatory exposure — NZ Privacy Act, health sector requirements, legal privilege obligations. Unclassified data is unprotected data.
2. AI oversharing — Rolling out Copilot without data classification means AI can surface HR records, financial forecasts, or board materials to anyone with a licence.
3. Data sprawl — As organisations grow, the volume of unclassified content compounds. Every month without action makes the problem harder to solve.

The good news: Purview’s AI classifiers make it realistic to classify terabytes of existing content, not just new files going forward.

How FutureIT Deploys Purview Classification

We’ve built a structured deployment process that takes organisations from zero classification to fully automated labelling:

Phase 1: Discovery & Assessment (Week 1–2)

• Audit your Microsoft 365 tenant for sensitive data exposure
• Run Purview’s built-in content explorer to identify where sensitive information already lives
• Map your regulatory and compliance requirements (Privacy Act, industry standards, client obligations)
• Review existing sharing permissions and oversharing risks

Phase 2: Label Architecture (Week 2–3)

• Design a sensitivity label taxonomy that matches your business — not an overly complex enterprise framework, but a practical set of labels your team will actually use
• Configure encryption, watermarking, and access restrictions per label
• Set up label policies — which users see which labels, mandatory labelling for certain locations

Phase 3: Classifier Deployment (Week 3–4)

• Enable relevant pre-trained classifiers across your tenant
• Train custom classifiers for industry-specific or organisation-specific content
• Configure auto-labelling policies that apply labels based on classifier output
• Test in simulation mode before going live

Phase 4: DLP & Monitoring (Week 4–5)

• Build Data Loss Prevention policies that trigger on labelled content — block external sharing, require justification, or alert administrators
• Set up DSPM dashboards for ongoing visibility
• Configure alerts for policy violations and unusual data access patterns

Phase 5: User Enablement & Copilot Readiness

• Train your team on how labels work and why they matter
• Roll out Copilot with confidence that sensitive data is properly classified and restricted
• Establish ongoing review cycles — classifiers improve with feedback, and new content categories emerge as businesses evolve

The Bottom Line

Microsoft Purview’s AI classifiers have crossed the threshold from “nice to have” to “essential infrastructure.” If you’re running Microsoft 365 — especially if you’re considering Copilot — content classification isn’t optional anymore.

The technology is ready. The deployment process is proven. And doing it now, before AI usage scales across your organisation, is significantly easier than retrofitting classification after the fact.

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Ready to classify and protect your data? Talk to our team about a Purview deployment tailored to your business, or explore our cybersecurity solutions to see the full picture.