Why Microsoft Purview matters for your business
What Purview actually does, where it sits in the Microsoft security stack, and why it is a prerequisite for AI adoption. Written for the people who have to justify the project.
The problem nobody talks about
Most organisations have no idea where their sensitive data is. Ask someone in leadership where all the customer PII lives, which employees have access to the board pack, or what data left the company last month. Without data governance in place, most teams struggle to answer any of these confidently.
This was manageable when work happened on a file server behind a firewall. It is not manageable when data lives across SharePoint, OneDrive, Teams, Exchange, and endpoint devices. The attack surface is everywhere. The visibility is nowhere.
What Purview actually does
Microsoft Purview is a data governance and compliance platform built into Microsoft 365. In practice it does three things:
It finds your sensitive data. Content Explorer and data classification scan your Microsoft 365 environment and tell you what sensitive information exists, where it is, and how much of it there is.
It protects your sensitive data. Sensitivity labels classify and optionally encrypt content. DLP policies detect and block risky sharing. Endpoint DLP extends this to devices. The protection follows the data, not the location.
It watches for risk. Insider Risk Management detects unusual data movement patterns, like an employee downloading hundreds of files before their last day. Purview surfaces these signals before the damage is done.
Where Purview fits in the security stack
Microsoft has four security pillars:
Entra handles identity. Conditional Access, MFA, identity governance. It controls the door.
Defender handles threats. Malware, phishing, compromised accounts. It is the alarm system.
Intune handles devices. Managed devices, enforced policies, allowed apps.
Purview handles data. What data you have, who can access it, where it is going, and who is doing something risky with it. This is the layer most organisations skip.
Most businesses invest in Entra and Defender but ignore Purview. They lock the door and install the alarm, but leave the filing cabinets open.
Why AI changes everything
You cannot deploy AI responsibly without data governance in place first.
Microsoft 365 Copilot searches content across your tenant using existing permissions. Every broken permission, every over-shared site, every link that was never revoked becomes a data exposure risk the moment Copilot is switched on.
A user asks Copilot to summarise the retention strategy and gets back salary bands from an HR spreadsheet they technically had access to for three years. Copilot does not create these problems. It exposes them.
Purview is how you fix this. Sensitivity labels classify content. DLP policies control what flows into AI prompts. Permission audits close oversharing gaps before Copilot can find them.
The business case
The biggest cost is the one nobody budgets for: the slow, steady leakage of sensitive data through normal business activity. An employee emails a client list to their personal address before leaving. A colleague shares a sensitive document with a vendor using a link that never expires.
Purview makes these risks visible and manageable. You move from hoping nothing bad happens to knowing what is happening.
For regulated industries: GDPR, HIPAA, PCI-DSS, and the EU AI Act all require you to know where sensitive data is, control access, and demonstrate compliance. Purview provides the technical controls and evidence.
Who needs to be in the room
Purview is not an IT project. IT and Security own the deployment, but they cannot design label taxonomies without knowing what the business considers sensitive. Legal defines retention requirements. HR needs involvement in Insider Risk Management. Compliance maps technical controls to regulatory obligations.
The best deployments start with a working group across all these stakeholders. The worst are where IT configures it in isolation and wonders why nobody uses the labels.
Where to start
You do not need to deploy everything at once. Start with visibility. Run Content Explorer to discover where sensitive data lives.
Then deploy labels. A simple taxonomy: Public, Internal, Confidential, Restricted. Publish with a sensible default. Get adoption before adding encryption.
Then add DLP. Start in simulation mode. Tune for two weeks. Enforce with user notification, not silent blocking.
Everything else builds on these foundations. Insider Risk works better when content is labelled. Copilot is safer when permissions are clean and labels are in place.
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