Private GPT

· 6 min read

Migrating From Copilot to Private AI

A practical playbook for moving off Microsoft Copilot to a private AI deployment: the usage audit, data mapping beyond Microsoft Graph, pilot, and rollout.

Moving off Microsoft Copilot is a different kind of migration than replacing a standalone chat tool, because Copilot is not a separate subscription you cancel in isolation. It is a feature layered into Word, Excel, Teams, and Outlook, licensed per user, and grounded only in whatever lives in Microsoft Graph. Teams that migrate cleanly treat it as a scoped project: audit what Copilot is actually answering today, map the data sources a replacement needs to reach, pilot alongside the existing licenses, then reassign seats once the pilot proves out.

1. Audit what Copilot is actually answering today

Find out which workflows people rely on Copilot for: drafting in Word, summarizing threads in Outlook, building slides, or asking questions that pull from SharePoint and OneDrive. Talk to the heaviest users in each department. The point is a short list of real workflows worth preserving, not an assumption based on what the license was sold to do.

2. Map the data sources Copilot cannot see

Copilot answers are grounded in Microsoft Graph: SharePoint, OneDrive, Exchange, and Teams. If your company's knowledge also lives in a CRM, a practice management system, industry specific software, or shared drives outside Microsoft 365, Copilot has never been able to answer from those sources at all. Use the migration to list every source a replacement should connect to, not just the Microsoft 365 content Copilot already covers, and decide which roles should be able to reach each one.

3. Run a pilot alongside Copilot, not instead of it

Pick one team or workflow and stand up the private deployment for that group while the rest of the company keeps its Copilot licenses active. Compare the pilot group's results against the workflows identified in step one: does it answer from the sources that actually matter, respect the access rules configured for that group, and hold up for the drafting and research work people already depend on.

4. Expand in phases, not all at once

Once the pilot group is satisfied, add departments in waves instead of switching the whole company on one date. Each wave surfaces a missing data source or an access rule that needs adjusting before it affects everyone, and it gives people time to build the habit of asking the new assistant instead of reaching for Copilot inside Office.

5. Reassign Copilot licenses last

Keep Copilot licenses active until the final wave confirms the private deployment covers its workflows. Copilot is usually billed per assigned user rather than as a single company wide subscription, so licenses can be reassigned or removed in the Microsoft 365 admin center gradually as each wave completes, rather than all at once. Migrating with an overlap period costs a stretch of double licensing cost and avoids the gap that pushes people back to pasting company information into a personal AI tool instead.

What changes once the migration is done

A completed migration replaces a feature scoped to Microsoft Graph with a standalone assistant connected to whatever sources your company actually uses, Microsoft or not, with access scoped by role and a model choice that is not fixed by a single vendor's product tier. The full comparison of Copilot against that model, on data scope, branding, and cost, is covered on the Private AI vs Microsoft Copilot page.

Book a meeting to map your team's current Copilot workflows to a pilot scope, including which sources beyond Microsoft 365, which users, and which access rules the deployment should start with.

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