Find the people who will make it useful

The trailblazer is not automatically the person who posts the most AI tips. Choose someone colleagues ask for help when a real task goes wrong. They know the work, can explain it without making others feel foolish, and will say when an answer is unreliable. That combination matters more than excitement.

Invite nominations from front-line managers and peers. Ask each candidate to show a recurring task they would improve, the source they trust, and an error they would refuse to pass along. The person who can say “this draft looks polished but the account number is wrong” is more valuable than someone who claims every process can be automated.

Do not staff the group only with experts or only with beginners. The expert knows exceptions; the newer employee reveals which instructions are hard to find. Include one thoughtful skeptic whose objections can be tested. Invite the information-security or data owner early enough to make a workable path, not just to veto the finished design.

A useful starter group might have a business owner who decides whether the result helps, a workflow expert who supplies good and bad examples, a learner who tests whether instructions make sense, a data or security partner who defines safe access, and a facilitator who records what changes. In a small company one person may hold two roles, but no role should disappear by accident.

Write the commitment down: perhaps two hours a week for four weeks, one office-hours session, a short failure log, and a demonstration using the team’s own work. If this work is simply added to a full day, the group will either quit or perform it invisibly. The manager must make room for it.

Do not appoint a champion as free technical support for an entire department. Give the group an escalation route for broken permissions, incorrect source data, and risky requests. The local guide should contain approved examples and a named contact. If every question waits for the champion, adoption becomes a bottleneck.

A ten-minute conversation is enough to expose the difference between useful curiosity and tool enthusiasm. Ask: “Show me work you would change. What would you leave to a person? What mistake would make you stop?” Listen for concrete records, customers, review steps, and the ability to revise a proposal. Beware of “we can automate everything” and “people just need to prompt better” when neither comes with a task or failure test.

When you announce the group, make participation open and practical. Explain the selection criteria and when another cohort can join. A secret “AI elite” can make hesitant employees less willing to ask questions. Trailblazers should shorten the distance between the first curious person and a safe, useful attempt.