Microsoft Purview Data Protection for AI Agents and Copilot 

AI agents do not use data the same way people do.

They read, summarize, generate, and move information across systems at machine speed. But most data protection controls were designed for employees, documents, and traditional applications, not autonomous agents, Copilots, and AI-powered workflows.

Fortytwo helps organizations establish a Microsoft Purview data protection and compliance model for AI interactions, so sensitive information used by Copilot, agents, and enterprise AI apps becomes discoverable, governable, and auditable.

The reality check

“We have Purview” is no longer a complete answer once AI agents are in the loop.

Microsoft Purview may already give you labels, DLP, audit logs, and compliance tooling, but AI changes the risk model.

Sensitive data can be exposed through prompts, summaries, generated output, plugins, connectors, or overshared content that becomes easier for Copilot and agents to discover.

Can you prove what happened when AI touched it?

Which sensitive data was available to Copilot or an agent?
Which AI interactions included regulated or confidential information?
Which prompts, responses, files, users, and systems were involved?
Was the exposure prevented, detected, logged, retained, and investigated correctly?
Are gaps in platform coverage documented as governance risks?

The Solution

Compliance that follows the data. 

Fortytwo helps you: 

Define sensitivity label taxonomy aligned to AI usage scenarios. 
Configure labels and label policies for AI-relevant workloads. 
Design and deploy DSPM (Data Security Posture Management) for AI where applicable (start with discovery, assessment and monitoring first). 
Enable AI interaction discovery and risk insights where supported. 
Design DLP policies for AI interactions (Copilot, agents, supported channels). 
Define AI interaction evidence handling (RBAC, retention, investigation, access, export rules).
Establish an oversharing remediation approach proper to AI scale-out. 
Integrate Purview signals with SIEM/investigation workflows (high-level). 
Capture known platform constraints and gaps as governance risks.  

What We Deliver


A Microsoft Purview operating model for AI compliance

Sensitive data usage in AI interactions becomes visible and measurable, and AI data risks are governed using audit-ready evidence. Oversharing becomes identified before AI amplifies it, and compliance 
teams can investigate AI interactions using native tooling. 

AI Data Protection Design

You get a practical data security and governance design for AI usage, with Data Security Posture Management introduced through discovery, assessment, and monitoring before enforcement. 

Labels and DLP Controls

Sensitivity labels and DLP policies are configured for Copilot, agents, and supported channels, helping protect AI-related data flows, prompts, responses, files, and interaction.

AI interaction evidence model

We define how AI interaction evidence should be handled, including RBAC, retention, investigation access, exports, and security boundaries.

Controlled path from audit to enforcement

You get a staged deployment plan that moves from discovery and audit-only monitoring to policy enforcement in a controlled way, reducing disruption and avoiding unexpected business impact.

AI risk and compliance review

Purview risk signals are mapped to your AI governance model, with known platform constraints and gaps documented as governance risks for decision-making and follow-up.

Who is this for?

This service is for security, compliance, and Microsoft 365 teams that are rolling out Microsoft 365 Copilot, Copilot Studio agents, or enterprise AI apps and need to prove that sensitive data remains protected, monitored, and auditable.

Common usecases:

Preparing Microsoft Purview for Microsoft 365 Copilot rollout.
Auditing sensitive data in AI prompts and responses.
Designing DLP policies for Copilot and AI agents.
Reducing oversharing before AI amplifies it.
Building an investigation model for AI interaction evidence.
Mapping AI data risks to compliance and governance requirements.

How we work

We start with current-state discovery.

Fortytwo reviews your Microsoft Purview setup, AI workload inventory, labels, DLP policies, audit configuration, and investigation requirements. We identify where AI interactions create new risks and where your current controls need to be adjusted.

Then we design the AI compliance model.

This includes sensitivity label taxonomy, DLP design, DSPM/DSPM for AI configuration, evidence handling, investigation workflows, and SIEM integration patterns.

Next, we deploy in audit-first mode.

You see exposure, oversharing, and risky AI interactions before enforcement is introduced. Once the structure is approved, we help you move toward enforcement in a controlled way.

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FREQUENTLY ASKED QUESTIONS

FAQ

Book a discovery call

Talk to us

Book an AI compliance discovery call and get a clear view of where your current Purview setup is ready for AI, and where it needs to be strengthened. 

Harri Jaakkonen
Principal Security Engineer 
oi.owtytrofobfsctd-603d80@nenokkaaj.irrah 

Every agent leaves a trail, so make certain it’s auditable. 

Harri Jaakkonen
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