AI Champions: Your Secret Weapon for Adoption
Champions are peer advocates who accelerate AI adoption from the inside. Learn how to build, run, and measure a champions program that drives real usage.
What are AI champions?
Champions are the people in your office who get excited about AI and help everyone else get excited too.
Imagine you just got a new phone feature. Would you rather learn about it from a 50-page manual or from a colleague who says “Hey, look at this cool trick I found”? That colleague is a champion.
Champions aren’t IT support. They’re regular employees who use AI in their daily work, share tips with their teammates, and help people who are stuck. They make AI feel approachable, not scary.
Champions vs IT support
This distinction matters for the exam. Champions and IT support serve different functions.
| Feature | Focus | When they help | How they help |
|---|---|---|---|
| AI champions | Cultural adoption — making AI part of how people work | Daily workflow: 'How can I use AI for this report?' | Peer coaching, tips, demonstrations, prompt sharing, encouragement |
| IT support | Technical function — making AI tools work correctly | Technical problems: 'Copilot isn't loading in my Teams' | Troubleshooting, access provisioning, configuration, bug escalation |
A champion might show a colleague how to use Copilot to draft a project update. IT support fixes the issue when Copilot doesn’t appear in someone’s Word ribbon. Both are essential, but they’re different roles.
Exam tip: Champions are about CULTURE, not TECH
If an exam question describes a user struggling with how to USE AI effectively, the answer involves champions. If the user has a technical problem (installation, access, errors), the answer involves IT support. Champions handle the “how do I get value from this?” questions.
Building a champions program
Step 1: Select champions
Not everyone is the right fit. Look for people who are:
- Enthusiastic about AI (genuine interest, not just compliant)
- Respected by peers (their advice carries weight)
- Diverse in role, location, and department (represent the whole organisation)
- Willing to invest time (2-4 hours per week alongside their regular job)
Avoid selecting only the most technical people. The best champions are often non-technical employees who have found practical ways to use AI in their daily work. Their stories are more relatable.
Step 2: Train champions
Champions need deeper knowledge than regular users:
| Training area | What champions learn |
|---|---|
| Advanced prompting | Techniques beyond basics — chaining, few-shot examples, context setting |
| Use case discovery | How to identify AI opportunities in any workflow |
| Responsible AI principles | So they can answer ethics questions from colleagues |
| Common objections | How to respond to “AI makes mistakes” and “I don’t trust it” |
| Escalation paths | When to refer issues to IT support vs the adoption team |
Step 3: Define responsibilities
Clear expectations prevent champions from burning out or doing too little.
What champions do:
- Hold weekly or fortnightly “AI office hours” for their team
- Share a prompt or tip of the week via Teams or email
- Run short showcase sessions (“Look what I did with Copilot this week”)
- Collect feedback from colleagues and relay it to the adoption team
- Report adoption blockers they observe on the ground
What champions do NOT do:
- Provide IT support (they redirect technical issues)
- Force people to use AI (they inspire, not mandate)
- Spend more than 10-15% of their work time on champion activities
Step 4: Recognise and reward
Champions are volunteering their time. Recognition keeps them motivated.
- Visible recognition: Mention champions in company meetings, newsletters, or leadership updates
- Exclusive access: Give champions early access to new AI features or tools
- Career development: Champion experience looks great on a CV — highlight it in performance reviews
- Community: Create a champions Teams channel for peer support, idea sharing, and camaraderie
- Small rewards: Swag, lunch vouchers, or conference tickets for top contributors
Rollout mechanics
Office hours
Champions hold regular drop-in sessions where colleagues can bring real work problems and get live help using AI.
Format: 30-minute sessions, weekly or fortnightly. No agenda — bring whatever you’re working on. The champion demonstrates how AI can help in real time.
Why it works: People learn best when they see AI applied to THEIR work, not generic demos.
Showcase sessions
Monthly 15-minute presentations where champions share real wins: “Here’s how I used Copilot to cut my weekly reporting from 3 hours to 30 minutes.”
Why it works: Social proof. When colleagues see a peer — someone with the same job — getting real value, they’re motivated to try.
Prompt libraries
Champions contribute to a shared prompt library — a collection of proven prompts organised by role and task.
Why it works: Removes the “blank page” problem. New users don’t have to invent prompts from scratch.
Measuring champion program success
| Metric | What it tells you | Target |
|---|---|---|
| Active AI users | Are more people actually using AI tools? | Month-over-month increase in teams with a champion |
| Usage frequency | Are users coming back after trying AI once? | Weekly active users as a percentage of total licensed |
| Champion engagement | Are champions staying active and motivated? | 80%+ of champions hosting at least one activity per month |
| User satisfaction | Do users find AI helpful in their work? | Survey scores improving quarter over quarter |
| Support ticket reduction | Are champions deflecting “how to” questions from IT? | Fewer basic AI queries hitting the help desk |
The champion-adoption correlation
Organisations with active champion programs consistently see 2-3x higher AI adoption rates in teams with champions compared to teams without. The champion effect is strongest in the first 90 days after deployment — the critical window when users either build habits or abandon the tool.
Scenario: Tomás’s 50-champion program at PacificSteel
🔄 Tomás needs to drive Copilot adoption across 5,000 workers in 12 factories and head office. He builds a champion program with a target ratio of 1 champion per 100 employees = 50 champions.
Selection: Tomás asks factory supervisors and department heads to nominate people who are “curious about technology and respected by their teams.” He gets 70 nominations and selects 50 based on diversity of role, location, and shift pattern.
Training: A two-day intensive (Day 1: advanced Copilot skills + responsible AI. Day 2: facilitation skills + objection handling). Then monthly 1-hour refresher sessions.
Rollout:
- Week 1-2: Champions use Copilot themselves. Build personal experience.
- Week 3-4: Champions start office hours in their teams.
- Month 2: First showcase sessions. Champions share early wins.
- Month 3+: Prompt library grows organically. Champions identify new use cases.
Recognition: Tomás creates a “Champion of the Month” award, shared in the company newsletter. Champions get branded mugs and early access to new AI features. The COO thanks champions by name in quarterly town halls.
Results at 6 months:
- Teams WITH champions: 72% weekly active Copilot users
- Teams WITHOUT champions: 28% weekly active Copilot users
- Champion-supported teams found 3x more use cases
Key flashcards
Knowledge check
One of Tomás's factory floor AI champions gets a question from a user: 'Copilot isn't appearing in my Word toolbar.' What should the champion do?
Tomás observes that teams with AI champions have 72% weekly active users while teams without champions have only 28%. What does this demonstrate?
Next up: Data, Security, Privacy and Cost — the four pillars every leader must assess before deploying AI.