Data Governance and Private AI on Microsoft 365: Practical Strategies for Swiss Companies

The shift towards widespread use of private AI in collaborative suites like Microsoft 365 presents unprecedented challenges for enterprise data governance. In Switzerland, where compliance with the nFADP and GDPR remains a high priority, the ability to protect, organize, govern, and derive value from data is no longer just an advantage—it's a prerequisite for successful AI projects and maintaining client trust.

At houle, we support organizations in the secure deployment of private AI solutions integrated with Microsoft 365, while adhering to the strictest Swiss standards in data governance. This article offers a comprehensive, pragmatic approach, illustrated with concrete cases, to help your organization transform data governance in the era of private AI.

1. Understanding New Data Governance Challenges with Private AI

The advent of private AI in office environments radically changes the data lifecycle. Documents, emails, or customer databases hosted in Microsoft 365 now become potential sources for custom artificial intelligence models, which themselves can create, process, or summarize ultra-sensitive content. Governance is no longer limited to static file classification or protection: it must continuously incorporate the use, transformation, and flow of information orchestrated by AI.

In Switzerland, the new Federal Act on Data Protection (nFADP) enforces strict control of data location, traceability, and minimization. To leverage AI on Microsoft 365 within this framework, it becomes crucial to finely map information flows, anticipate risks, and implement active supervision measures.

2. Mapping and Classifying Data in Microsoft 365

The first successful step in governance for the AI era is a comprehensive inventory of data under your organization’s responsibility. Microsoft provides native tools such as Microsoft Purview, enabling the identification of data types (personal, confidential, regulated, etc.) and automatic classification through proprietary AI engines. However, it is often necessary to supplement this approach with integration of private AI modules—for example, custom-developed add-ins hosted locally—to fine-tune the detection of sensitive data following logic specific to your sector or Swiss requirements.

It is recommended to start with targeted inventories: SharePoint, OneDrive, and Exchange. Next, use private AI to automate the detection of strategic data categories (for example: unpublished financial information, R&D results, client contracts). This facilitates the implementation of proactive, tailored management policies.

3. Implementing Effective Retention and Minimization Policies

Governance requires not only knowing what you own, but also managing the data lifecycle based on actual usage. Microsoft 365 enables the definition of retention and automatic deletion policies. When privately hosted (Swiss hosting), AI must comply with these same principles, avoiding any creation or use of fictitious or unnecessary data for model training.

The "privacy by design" principle, strongly endorsed by the nFADP, calls for close collaboration between M365 environment administrators, security teams, business units, and AI partners. The goal: retain only what is strictly necessary, limit file duplication for AI training, and document every automated extraction or process.

4. Securing Access and Tracking AI Use of Data

The granularity of access rights in Microsoft 365 must be preserved when private AI consumes or processes datasets. It must be ensured that only authorized models, hosted via secure solutions like Foundry or Azure OpenAI in dedicated instances, can access sensitive content.

Comprehensive audit logs of AI queries, interpretations, or generated summaries are essential to detect any security issues or incidents and provide evidence for compliance purposes. At houle, we systematically integrate advanced monitoring solutions based on Microsoft Graph APIs and “guardian” add-ins to safeguard confidentiality at every AI-M365 interaction.

5. Ensuring nFADP and GDPR Compliance in Private AI Use

Swiss privacy requirements impose strict rules: restriction of international transfers, reinforced consent, and documentation of processing in accordance with nFADP and GDPR. Private AI models used within Microsoft 365 must be fully audited and assessed before production, especially if they process personal data or profiling.

Sensitive information extracted or generated must be stored and used exclusively on infrastructure located in Switzerland, or at a minimum in the EU under validated legal frameworks. houle solutions allow hosting of LLMs (Large Language Models) and AI workflows on sovereign clouds, ensuring perfect alignment with the Swiss regulatory ecosystem.

6. Leveraging Private AI to Enhance Data Governance

Ironically, the rise of private AI is not just a governance threat, but also an optimization and value driver. AI-driven automation enables compliance gaps to be identified, misuse detected, orphan or redundant content spotted, as well as the suggestion of more efficient reorganization policies.

Many add-ins developed by houle leverage these features: semantic analysis to detect hidden private data in attachments or notes, intelligent classification suggestions, automated processing registers for DPOs, and proactive alerts for data leaving secure perimeters.

7. Best Practices for Effective Governance in the Private AI Era

• Involve the DPO (Data Protection Officer) and security management at the design stage of all embedded AI solutions on Microsoft 365.
• Choose partners with real expertise in Swiss frameworks (nFADP, FADP, local case law) for your AI and governance modules.
• Favor deploying AI on sovereign infrastructure, located in Switzerland or in the EU under robust contractual clauses.
• Implement regular audits: access checks, compliance reviews, model data use monitoring, systematic documentation of incidents or individual rights requests.
• Train all staff in new governance challenges in the AI era: short cycles, interactive tools, awareness on AI risks (leaks, hallucinations, bias, etc.).

Conclusion

Data governance at the heart of Microsoft 365 is undergoing a profound transformation with the adoption of private AI. For Swiss organizations, this evolution is not only a challenge but also an opportunity to gain agility, resilience, and trust. The combination of custom AI add-ins, sovereign hosting, and reimagined governance offers unique assurances. houle is positioning itself as the reference partner for this transformation, blending innovation and regulatory rigor.

References

• The new Swiss FADP (official explanations, admin.ch)
• Good governance solutions with Microsoft Purview (Microsoft Learn)

Practical tips for Microsoft/Azure

• Keep examples concrete: show 1-2 configuration steps (Azure resource, ask prompt), and test with a small dataset first.
• Prefer RAG (retrieval-augmented generation) for grounding answers: index internal docs, add answer citations and logging.
• Deploy models in a Swiss region for data sovereignty and enable proper moderation + access controls (Azure AD, role-based).