Champ-scan
AI CHAMPIONSCAPABILITY
Lauren Kelly
Purpose Spot the people colleagues already trust and badge them as AI Champions.
Intervention type Network-based selection
Lead Change lead or HR analytics partner
Time 2 h data pull · 60 min scoring workshop
Expected outcomes
Leaders: Data-backed list of high-reach influencers
Managers: 10% role carve-out approved for every champion
Org: 80 % of staff now have a champion inside their immediate network
What to bring to the session
Org and People Data: Slack/Teams data export, MS Viva reach report, Org chart layer heat map
Champion Role Card (Below)
Steps
1 | Map influence
Step 1: Spot your high-connectors
You’re looking for people who get mentioned often, answer questions, or are seen as go-to helpers. This step uses whatever digital trails you already have.
Where to look:
Slack or Teams:
Export channel data (most-used public channels or team spaces).
Look at mentions, reactions, and thread replies.
Tools like MS Viva, Slack Analytics, or Worklytics can show who’s active and who people reply to most.
Email or calendar metadata (optional):
Consider who gets looped in on collaborative threads or invites, but prioritise chat platforms where informal influence shows.
Manual manager pulse check (fallback):
Ask 3–5 managers: “Who do people ask when they’re unsure about AI or tools?” Log those names.
What to do next:
List your top 20-30 names based on mentions, responses, or visibility.
Load those names into your Influence Scorecard or Miro grid (one sticky per person).
Step 3: Launch a 3-question poll (anonymous)
“Who do you ask first when you’re stuck?”
“Whose advice do you trust on new tools?”
“Who helped you last week?”
Leave it open 24 h. Aim for ≥ 50 % response rate.
Export results directly into the scorecard.
2 | Score influence
Step 4: Drop top 50 names onto a grid type Influence Map
One sticky per name. Auto-fill Reach (interaction count).
Step 5: Score each on five factors (1-5)
Sum the five scores for a Total Champion Index. Highlight the top quartile.
If they score top for everything and 1 for AI-in-Role, seriously consider if they are the right choice. Or how you can grow their AI confidence before adding them to the AI Champions.
Step 6: Run the diversity checklist
≥ 40 % frontline / customer-facing
≥ 3 business units represented
Junior, mid, senior levels represented
Remote, hybrid and or shift workers included
Gender balance roughly reflects org
At least one champion per major region
Adjust if any box is red.
3 | Invite & confirm
Step 7: Send Champion Invite
Email them direct
Attach the Champion Role Card (10 % time commitment, demo kit, KPIs).
Copy line-managers with the Manager Message Kit (“why this matters” bullets).
Step 8: Track replies
Mark “YES”, “NO”, “Maybe” on the scorecard.
Need replacements? Go to the next person on the list.
Step 9: Post the Influence Heatmap
Export the map as a PNG.
Share in #ai-champions and the exec channel.
Add a short line for leaders to quote:
“These are the trusted voices guiding our AI shift.”
Step 10: Log champion density
Number of employees ÷ champions per unit.
Monitor quarterly; aim for < 25 people per champion.
Resources
Champion Role Card
One-pager PDF / slide
Purpose: “Be the trusted peer who turns AI ideas into real practice.”
Time: ~10 % of weekly hours (≈ ½ day)
Key actions
Run one 15-min micro-demo each fortnight
Collect 2 short success stories per month
Feed blockers to the AI adoption squad
Support you get
Starter demo kit
Monthly champion clinic
Exec shout-outs & mini-budget for experiments
Success measures
3+ demos run in first quarter
50 % of your team tries at least one demo move
Story posted in #ai-wins every month
Who to contact: Change lead | Slack @AI-Champ-Support
Manager Message Kit
Subject: Your team member has been nominated as an AI Champion
Key bullets for managers
Why it matters
Champions shorten the “learn → use” gap and cut support tickets by up to 30%.
Time ask
10 % role carve-out (approx. half-day/week) for three months.
What success looks like
More peer-led demos, faster AI uptake, documented time savings.
Your role
Protect the time.
Cheer loud wins at stand-ups.
Share blockers with the adoption squad.
FAQs
Will outputs drop? Evidence shows productivity rises once champions start sharing quick wins.
How is progress tracked? Influence Scorecard + monthly metrics slide.
What if the workload spikes? We pause or rotate champions; just flag it.
Other methods within the capability block
Human-AI Performance
By Lauren Kelly
Contact: lauren@alterkind.com
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Human-AI Performance™ is a proprietary methodology developed by Alterkind Ltd using our Behaviour Thinking® framework. All content, tools, systems, and resources presented on this site are the exclusive intellectual property of Alterkind Ltd.
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Thanks to Nicholas Edell, Valentina Tan and multiple VPs implementing AI for your feedback during development.
LICENSE
Human AI Performance by Alterkind is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Based on work at alterkind.com
For commercial licensing contact: lauren@alterkind.com