In every team, a few people figure out new tools first. Others watch them, ask questions and copy what works. That’s how adoption really spreads.
An AI champions program makes that deliberate.
What champions do
- Help colleagues with questions and practice.
- Find and share wins — workflows that save real time.
- Grow the shared library of prompts and workflows.
- Spot risks — data mistakes, over-reliance, quality issues.
- Bring feedback to leadership about what’s working and what isn’t.
Choosing champions
Look for:
- Curiosity — they experiment.
- Credibility — peers respect and listen to them.
- Patience — they enjoy helping.
- Judgment — they take data and quality seriously.
Technical skill helps, but it’s not the main qualification. A respected office manager who’s curious will often outperform a tech enthusiast nobody listens to.
Give them what they need
- Time. Protected hours each week. Champions without time become frustrated champions.
- Early access to tools and features.
- Training a step ahead of the rest of the team. See AI literacy.
- A direct line to leadership.
- Recognition. Public credit for their work.
The champions’ scoreboard
Champions need a simple way to show progress. Track behaviors, not just logins:
- Workflows added to the shared library
- Colleagues helped
- Tasks moved to AI across their team
- Issues caught and fixed
- Wins shared in meetings
This fits naturally on your weekly Scoreboard in the BOSS framework.
The weekly rhythm
- Team meeting share-out: one win, one lesson.
- Champion huddle: a short weekly call among champions to swap what’s working.
- Office hours: a regular time colleagues can drop in with questions.
- Monthly review with leadership: adoption, risks, next priorities.
The shared library
The library is the champions’ most lasting contribution. Organize it by role and task: “Sales – follow-up after estimate,” “Service – reschedule reply,” “Ops – daily job report from voice memo.” Each entry includes the prompt or workflow, an example output and notes on what to check. Store it in your AI second brain.
Champions and agents
As your business adds AI agents, champions often become their first human owners — the people who monitor an agent’s work, refine its instructions and flag problems. Every agent needs a named owner on the Ownership Chart. See AI and human team structure.
Common mistakes
- Choosing champions only for technical skill.
- No protected time.
- No recognition.
- Letting champions become the only people who use AI.
- No feedback loop to leadership.
A champion’s first month
Week 1: Get trained a step ahead and pick two workflows to master personally. Week 2: Help three colleagues each hand one real task to AI. Week 3: Add the best workflows to the shared library with examples and notes on what to check. Week 4: Share results at the team meeting and bring leadership a short list of what’s blocking adoption.
That simple rhythm builds momentum quickly and gives the champion visible wins to point to.
Questions champions should bring to leadership
- Which tools or features would free up the most time if approved?
- Where are people unsure about the policy?
- Which tasks are people trying to hand to AI that need a better process first?
- Who on the team is struggling and needs more support?
Starting small
You don’t need a formal program on day one. Pick one or two champions, give them a few hours a week and a simple scoreboard, and start the weekly share-out. Expand as it works. See AI training for employees.
How leaders support champions
Leaders make or break champion programs. Attend the share-outs. Ask champions what’s blocking adoption and remove those blockers. Use AI visibly yourself. Approve tools and access quickly when champions find something useful. And protect champions’ time when the busy season hits — that’s exactly when the program is most likely to quietly die.
When champions rotate
Champions burn out if the role never ends. Consider rotating the role every few quarters, with outgoing champions mentoring the new ones. Rotation spreads skill across the team and keeps energy high.
What success looks like
Within a few months, a healthy champions program shows up in small ways: people ask “can AI do this?” before starting a repetitive task, the library grows every week, new hires learn AI as part of onboarding and leaders hear about wins without having to ask. That’s when AI has become part of how the business works. See leading an AI-first team.
For help building an AI-first operating rhythm, see Chief or contact Ben.
Next steps
Read AI workshop for teams and AI training for employees.
Questions people ask
What is an AI champion?
An AI champion is a team member who is a little ahead on using AI, has time set aside to help colleagues, shares what works and brings feedback to leadership. Champions accelerate adoption from within each team.
How do you choose AI champions?
Look for curiosity, credibility with peers, patience and good judgment about risk — not just technical skill. One champion per team or department is a good starting point.