Start with Repetitive Questions, Not with Technology
Before evaluating tools, find where the team repeatedly answers the same questions: • HR answering the same policy queries weekly • Customer service explaining standard procedures • New staff looking for process documentation • Sales searching for product specifications
Define the Document Scope
Do not feed every document into AI on day one. Start with a focused set: • One department\'s most-referenced documents • The top recurring questions your team answers • Documents that are relatively stable (not changing daily)
Pilot with a "Small but Accurate" Approach
Deploy a knowledge assistant for one department or use case. Measure: • How many queries it resolves successfully • Answer accuracy (with source references) • Time saved for the team • What must improve before scaling
Then Decide Whether to Scale
Pilot results give concrete data to justify further investment — or to adjust the approach before broader rollout.
A practical 30-day document MVP
In week one, choose one department and one library, then remove duplicates and obsolete versions. In week two, define real questions, access roles and expected sources. In week three, let a small user group test every answer against the documents. In week four, classify incorrect answers, missing answers, version problems and review effort. A named document owner should approve changes each week so the technical team never decides business truth by default.
Make only three decisions at day 30
Decide whether the questions recur often enough to justify the service, whether answers and sources meet the agreed threshold, and whether owners can maintain the library. Expand only when all three are true. If one fails, repair the content process or stop. This controlled rhythm may look slower than importing a shared drive, but it exposes the causes that determine long-term quality.
Practical next step
- Free AI & Workflow Project Planner: Turn the library, questions, roles, reviewer and 30-day measures into a one-page plan.