In five steps: decide which documents belong in, clean and deduplicate them, fix permissions, connect an AI tool that reads from that store, and pilot with one team before rolling out. The cleaning step is where most projects succeed or fail - the technology is the fast part.
Step 1: Decide what belongs in
Not everything. Start with the documents people actually search for: process descriptions, product documentation, project templates, decisions, FAQs, policies. Personal drafts and archive dumps stay out at first.
Step 2: Clean before you connect
Deduplicate: three versions of the same procedure produce three different answers.
Archive or mark outdated content; the AI cannot smell stale documents.
Fix titles and file names - retrieval leans on them heavily.
Convert scans to real text where the content matters.
Budget days to weeks for this on a typical SME document estate. It is unglamorous and it is the project.
Step 3: Get permissions right first
AI tools answer only from what the asking user may already see - which means every over-shared folder becomes visible. Review sharing on the folders going in: remove "anyone with the link" where it does not belong, check guest access, mark sensitive directories.
Step 4: Choose the AI layer
Three honest options:
Use what you already pay for: Microsoft 365 Copilot for Microsoft shops, Gemini for Google Workspace shops.
Knowledge-base tools with built-in AI: Notion AI and similar, when your knowledge base lives there anyway.
A custom retrieval setup (RAG) when you need specific hosting, Swiss data residency, or sources across several systems.
Step 5: Pilot with one team
Pick a team with real questions and decent documents. Run 2-4 weeks, log which answers were right and which missed, fix the content - then widen. A pilot with 20 people tells you more than a rollout to 200.
Sources
IBM, "What is RAG (Retrieval-Augmented Generation)?" (accessed 20 October 2026)
Microsoft, "Data, Privacy, and Security for Microsoft Copilot" (accessed 20 October 2026)
Notion, "Notion AI security & privacy practices" (accessed 20 October 2026)
Last updated: 20 October 2026.
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