Overview

Your most senior SysAdmin is nervous. You just asked her to be the AI champion for incident management. The AI tool has only been out for a month. She's still learning it herself. "What if I screw this up?" she asks.

That question tells you she's the right person.

The best champions aren't the ones who know everything about the tool. They're the ones who respect their peers, care about getting it right, and are willing to be the bridge between new technology and skeptical teams.

By the end of this lesson, you'll understand what makes a good champion, how to select and support them, and how to scale from individual champions to organization-wide adoption.

Purpose

A champion is not a trainer. A champion is a peer who has figured out how to use the new technology well and helps their colleagues do the same.

Champions create adoption at scale. One manager can mandate that people use a tool. One hundred champions across the organization can make it so compelling that people want to use it.

Why This Matters

Champions compress adoption timelines dramatically.

Without champions:

• Change is top-down and slow
• Teams resist because they don't see peer buy-in
• Misconceptions persist because people ask a trainer, not a peer
• Adoption plateaus at 60-70% (the mandatory level)
• You need a formal training program to maintain adoption

With champions:

• Change is peer-driven and fast
• Teams adopt because their trusted peers are using it
• Questions are answered quickly by people who understand their context
• Adoption reaches 85-90%+ (people want to use it)
• Training is sustained by champions, not formal programs

The difference in business value is dramatic. A well-run champion program is worth more than a big training budget.

Core Concepts

Key Insight: The Champion Model

A champion program has a clear structure and clear roles.

Selection (Who?)

• Respected by peers (not necessarily the most technical, but someone people listen to)
• Mid-level or senior (credible on technical matters)
• Pragmatic (cares about what works, not ideology)
• Open to change (willing to try new things)
• Communicative (willing to share what they learn)
• Diverse roles (you need champions across different functions, not just from one team)

Enablement (Support)

• Early access and training (they learn before everyone)
• Time allocation (20% during first 3 months, 10% ongoing)
• Resources (tool access, documentation, vendor support)
• Authority (they can make decisions about their area)
• Recognition (public visibility, career benefit)

Engagement (What They Do)

• Learn the tool deeply (become subject matter experts)
• Identify use cases (find problems the tool actually solves)
• Support peers (answer questions, help with problems)
• Provide feedback (honest assessment of what's working)
• Advocate (share wins and successes)

Scaling (Growth)

• Start with 5-10 champions across the organization
• After 3 months, recruit new champions (second wave)
• After 6 months, move to peer mentoring model (champions train their teams)
• After 1 year, the tool becomes "just how we work" (champions become specialists, not advocates)

Key Insight: Selection Criteria

Choosing the right people as champions is critical. Bad champion choices doom the program.

Who to select:

• The respected peer: Someone people consult for advice. They don't need to be the smartest in the room, but people trust their judgment.
  -
  Example: "When I'm not sure whether to escalate a ticket, I ask Sarah."
• 
  The early adopter: Someone who's already trying the new tool on their own. They're curious and willing to experiment.
• 
  Example: "I noticed Marcus has been playing with the AI tool. Let's ask him to be a champion."
• 
  The skeptic: Someone who's skeptical but willing to try. When a skeptic buys in, they become the most powerful advocate.
• 
  Example: "James was resistant at first. He understood the concerns better than anyone. Now he's our biggest champion."
• 
  The connector: Someone who crosses teams or functions. They can spread adoption across boundaries.
• 
  Example: "Alex works between the network team and the infrastructure team. Having them as a champion spreads adoption everywhere."
• 
  The diverse perspective: Champions should represent different roles, levels, and backgrounds. Diversity ensures the tool gets adopted well across the organization.

Who not to select:

• Someone who's mandated by management ("The IT director said you're the champion")
  - Someone already overloaded (they'll burn out)
  - Someone who's too busy learning the tool themselves (they can't help others yet)
  - Someone who doesn't want the role (unwilling champions become resentful)

Key Insight: The Champion Selection Process

Don't just appoint champions. Make an offer. Get consent.

Process:

• Identify candidates: (2-3 potential champions per team)
  - "Who does your team trust for advice?"
  - "Who's already interested in the new tool?"
  - "Who's skeptical but open?"
  -
  "Who crosses teams?"
• 
  Approach individually: (1-on-1 conversation)

"We're rolling out this AI tool, and I think you'd be a great champion. That means you'd learn it deeply, help your teammates figure it out, and give us feedback on what's working. You'd have dedicated time (20% for the first 3 months), access to training and resources, and I'd recognize it publicly. Interested?"

• 
  Explain the time and support: (be honest)

"This will take 20% of your time for the first quarter. You'll get training before everyone else, you'll have direct access to our support team, and you'll be part of a champion network learning together. After the initial ramp, it drops to 10%."

• 
  Listen to their concerns: (take them seriously)

"I'm worried I'll mess it up." / "You probably will at first. That's fine. We'll learn together."

"What if my team doesn't listen to me?" / "Good question. Let's talk about how to help your team see the value."

• 
  Get their commitment: (don't force it)

"I'm in" / "Let's do this."

"I'll think about it" / "Take a week. Let me know."

"I don't think so" / "That's OK. I hear that. Can I ask why? Maybe we're solving the wrong problem."

Champions work best when they volunteer, not when they're drafted.

Key Insight: Supporting Champions

Champions will fail if you don't support them well.

Support must include:

• Early training: They learn before everyone (2-3 weeks early)
  - Deep access: They get to try everything, including advanced features
  - Direct support line: They can reach the vendor or a technical expert quickly
  - Dedicated time: Protected time in their calendar (20% is realistic)
  - Peer network: Monthly champion roundtables where champions share with each other
  - Resources: Documentation, templates, lab environment
  - Recognition: Public visibility, career credit, possibly financial compensation

Support might look like:

Month 1:

• 3-day intensive training (champion-only)
• Hands-on labs
• Deep exploration of the tool
• Weekly check-ins with you

Month 2:

• Additional training (advanced features)
• First attempts supporting peers
• Weekly champion roundtable
• Feedback on what's working

Month 3:

• Leading peer training
• Supporting more teammates
• Identifying best practices
• Monthly champion roundtable

Month 4+:

• Ongoing peer support
• Monthly deep dives on new topics
• Champion recognition

Key Insight: What Champions Actually Do (Operationally)

Champions don't just exist. They have concrete responsibilities.

Daily/Weekly (Champion's Job):

• Answer questions from peers (in person, in Slack, via email)
• Model good usage (people watch to see how champions use the tool)
• Troubleshoot problems ("Why isn't this working?")
• Share tips and tricks ("You can do it faster if you...")
• Identify gaps ("This use case isn't covered by the tool")

Monthly (Champion's Contribution):

• Lunch-and-learn: 30 minutes teaching a specific topic to the team
• Best practices documentation: "Here's how to do X well"
• Feedback to leadership: "Here's what's working, what's not"
• New champion recruitment: "I found someone who should be a champion"

Quarterly (Champion's Leadership):

• Participate in champion roundtable
• Help evaluate new tool versions or features
• Support new team members onboarding to the tool
• Advocate for process improvements

This is substantial but not overwhelming.

Key Insight: Recognition and Incentives

Champions need to be recognized. If being a champion is all work and no visible benefit, people won't do it.

Recognition strategies:

• Public visibility: Call out champions in team meetings, in newsletters, on internal comms
  - Career benefit: Make champion experience valuable on resumes, in promotion conversations
  - Financial compensation: Bonus, raise, or compensation for the extra work (depends on your organization)
  - Specialized role: "AI Operations Specialist" or "AI Champion" becomes a formal position
  - Professional development: Champions get priority access to training and conferences
  - Network: Champions join an exclusive internal community with direct access to leadership

Don't under-invest in recognition. If people feel their champion work is invisible, it stops.

Key Insight: Scaling From Individual Champions to Organization-Wide Adoption

As adoption spreads, the role of champions evolves.

Phase 1: Launch Champions (Months 1-2)

• Goal: Get the tool off the ground
• Champions: 5-10 across the organization
• Focus: Learning, peer support, identifying use cases
• Your role: Direct support, removing blockers

Phase 2: Champion Expansion (Months 3-4)

• Goal: Spread adoption to every team
• Champions: 15-20, including second-wave recruits
• Focus: Training peers, developing best practices
• Your role: Champion roundtables, recognizing success

Phase 3: Peer Mentoring (Months 5-6)

• Goal: Make the tool normal
• Champions: 25-30, embedded in teams
• Focus: New hire training, advanced use cases
• Your role: Steering, addressing systemic issues

Phase 4: Specialist Model (Month 6+)

• Goal: Champions become specialists
• Champions: 10-15 deep experts, many peers using tool independently
• Focus: Advanced integration, optimization, supporting other teams
• Your role: Strategic guidance, resource allocation

Each phase has different champion needs and different success metrics.

Practical Use Cases

Use Case 1: Recruiting Your First Champions

Scenario: You're rolling out an AI incident management tool. You need champions.

Process:

Step 1: Identify candidates (in conversation with team leads)

• "Who on your team would be great at this?"
• "Who's curious about new tools?"
• "Who do people actually listen to?"

Step 2: Approach each candidate individually

• "I'm looking for champions for the new AI incident management tool. You came up in conversations with your team lead. Would you be interested?"
• Listen to their response. If hesitation: "What's your concern?"
• Address concerns: "You'd have dedicated time. We'd train you first."

Step 3: Those who say yes enter the champion program

• Schedule intensive training (2-3 days before the rest of the team)
• Introduce them to each other (build the champion peer network)
• Explain expectations: "You'll learn it first, help your team, give feedback"

Step 4: Those who need more info

• Offer trial period: "Be a champion for the first month. If you hate it, we'll find someone else."
• Show examples: Tell them about champions from other rollouts
• Talk to previous champions: "What was it actually like?"

Step 5: Those who say no

• Respect their decision: "That's OK. Can I ask why?"
• Keep them in mind: "If you change your mind in a month, let me know."
• Have a backup list of potential champions

Result: You have willing champions, not reluctant ones.

Use Case 2: Running a Monthly Champion Roundtable

Scenario: You're supporting 12 champions across the organization. You need them to stay connected and informed.

Monthly Roundtable Structure (1.5 hours, virtual or in-person):

Part 1: Wins and Challenges (30 minutes)

• Each champion shares one success: "Here's something that worked really well"
• Each champion shares one challenge: "Here's where I got stuck"
• Goal: Learn from each other, surface patterns

Part 2: Topic Deep Dive (30 minutes)

• One topic relevant to multiple champions
• Vendor rep or you lead discussion
• Q&A on specific technical or process questions

Part 3: Planning (20 minutes)

• What's coming next month?
• What do champions need to know?
• Any tool updates or changes?
• New team members joining who need champion support?

Part 4: Recognition (10 minutes)

• Highlight a champion's contribution
• Share a story of adoption success
• Celebrate together

Outcomes:

• Champions feel connected to each other
• Problems are caught early
• Best practices are shared
• You stay informed about what's actually happening

Use Case 3: Transitioning From Launch Champion to Specialist

Scenario: It's been 4 months. Your champion, Marcus, has helped his team adopt the AI tool successfully. Now adoption is spreading to other areas, and you need to evolve his role.

Conversation with Marcus:

"You've done an amazing job with your team. Adoption is at 85%, and people actually understand how to use the tool well. I want to talk about what's next for you.

Option 1: Keep supporting your team, but dive deeper into advanced use cases. Become the person your team goes to for complex problems.

Option 2: Expand your scope. Start supporting other teams who are behind on adoption.

Option 3: Formalize your role. Become an 'AI Operations Specialist'. This becomes part of your job description, with appropriate compensation.

What appeals to you?"

Marcus responds based on his interest. Some champions want to go deep on their team. Some want to expand. Some want a formal role. All are valuable.

Result: Champion role evolves as the program matures. Champions stay engaged longer.

Examples

Example 1: A Champion Role Description

Title: AI Operations Champion

Reporting: To their functional manager; matrixed to the AI Operations Lead

Time Commitment:

• Months 1-3: 20% of work week
• Months 4-6: 10% of work week
• Month 6+: 5-10% of work week (as needed for new team members, complex issues)

Responsibilities:

1. Learning & Mastery

• Complete all champion training
• Practice on real scenarios
• Stay current on tool updates and new features
• Deep understanding of the tool's capabilities and limitations
• Peer Support
  - Answer peer questions (in person, in Slack, via email)
  - Help troubleshoot problems
  - Pair with struggling teammates
  - Share tips and tricks
  -
  Response time target: Same day for most questions
• 
  Team Education
• Lead monthly lunch-and-learns
  - Create documentation and guides
  - Conduct one-on-one training as needed
  - Help onboard new team members
  -
  Review peers' usage and provide coaching
• 
  Feedback & Improvement
• Report problems and limitations
  - Suggest feature improvements
  - Participate in monthly champion roundtables
  - Help evaluate tool updates
  -
  Contribute to best practices documentation
• 
  Advocacy
• Share wins and successes
  - Demonstrate value to skeptics
  - Mentor new champions
  - Support adoption in adjacent teams

Recognition:

• Public recognition in team meetings and company comms
• Career benefit: Experience counts toward promotions
• Potential bonus based on adoption metrics
• Access to professional development and training

Success Metrics:

• Team adoption rate (target: 80%+ in first 2 months)
• Peer satisfaction (target: 80% rate champion as helpful)
• Tool usage quality (target: 80%+ of recommendations followed correctly)
• Questions answered (target: 24-hour response for peer questions)

Example 2: A Champion Recruitment Email

Subject: Be an AI Ops Champion (+ dedicated time & recognition)

Hi [name],

We're rolling out an AI incident response tool across IT Ops, and we're looking for champions. Your name came up as someone who's respected by your peers and pragmatic about new tools.

Here's what I'm asking:

The Role:

• Learn the tool deeply before the rest of the team
• Help your teammates figure it out
• Share what you learn
• Give us honest feedback on what's working and what isn't

The Time:

• 20% of your time in the first 3 months
• 10% after that
• Dedicated time in your calendar (not on top of your normal work)

The Support You'll Get:

• Intensive training before everyone else (2-3 days)
• Direct line to technical support
• Monthly champion roundtables (connect with other champions)
• All resources you need to help your team

The Recognition:

• Public visibility and thanks
• Career credit (this goes on your resume and in promotion conversations)
• Potential bonus for driving adoption
• Formal "AI Ops Champion" title

Why This Matters:

Your team trusts you. If you're using the tool and finding value, they will too. You'll be the difference between adoption and resistance. And you'll build a valuable new skill.

Next Steps:

Let's grab 30 minutes and talk through it. No obligation. Just a conversation to see if it's the right move for you.

[Calendar link]

Looking forward to talking.

Example 3: A Champion Success Story (What to Communicate)

Internal announcement:

Subject: Meet Sarah, Our AI Ops Champion

Sarah has been the AI incident response champion for the infrastructure team for the past 3 months. Here's her impact:

• Team adoption: 87% of her team uses the tool daily (target was 80%)
  - Usage quality: 85% of AI recommendations are being followed, indicating strong confidence
  - Problem-solving: Sarah identified three bugs in the initial tool that the vendor has now fixed
  - Knowledge sharing: She's conducted 4 lunch-and-learns attended by people across multiple teams
  - New champion: Sarah has identified and recruited the next champion for the network team

What does Sarah say about the experience?

"I was skeptical at first. The tool seemed like it could replace judgment. But as I used it, I realized it's actually the opposite. It handles routine analysis so we can focus on the complex problems. My team got better faster because we had actual evidence that it works, not just a mandate."

Thanks, Sarah. You're exactly the kind of peer leadership that makes these transitions successful.

To anyone else considering being an AI champion: We're recruiting more. It's rewarding, you get dedicated time, and you learn a valuable new skill. If interested, let me know.

Anti-Patterns

Anti-Pattern 1: Drafting Champions Instead of Recruiting Them

The trap: You decide on champions and announce them without asking. "You're the AI champion for your team, effective immediately."

Why it fails: Unwilling champions are resentful. They go through the motions but don't advocate. Their teams sense the reluctance.

Fix: Approach people. Make an offer. Get consent. Respect if they decline.

Anti-Pattern 2: Champions Without Time

The trap: You ask someone to be a champion but don't free them from their normal work. "Champion is on top of everything else."

Why it fails: Champions burn out. They do a bad job because they're spread too thin. They resent the extra work.

Fix: Protect champion time. 20% in the first quarter is real time, not "when they can get to it."

Anti-Pattern 3: Champions Without Support

The trap: You select champions and then leave them alone to figure everything out.

Why it fails: Champions struggle with the tool and can't help their teams. They look bad and people lose confidence.

Fix: Support champions intensively. Train them first. Give them direct access to help. Check in regularly.

Anti-Pattern 4: No Recognition

The trap: Champions do significant extra work and get no acknowledgment. They become known for supporting the tool, not for their normal work.

Why it fails: They feel unappreciated. They stop helping once the mandate is fulfilled. Future champion recruitment is harder.

Fix: Recognize champions visibly and meaningfully. It doesn't have to be monetary, but it has to be real.

Anti-Pattern 5: Static Champion Role

The trap: You select champions for launch and they stay in that role forever, even after the tool is mature and adoption is done.

Why it fails: Champions get tired of the role. The tool doesn't need champions anymore (it's normal). Champions feel trapped.

Fix: Evolve champion roles. From launch → support → specialist → mentor. Champions' responsibilities change as the tool matures.

Human Judgment Checkpoints

• Talk to champions: Are they still engaged and motivated? Or are they starting to feel burned out?
  - Talk to peers: Do people see champions as helpful or as tools of management?
  - Check adoption metrics: Are champions' teams adopting faster and better than non-champion teams?
  - Listen to feedback: What do champions say is working? What's frustrating them?
  - Review recognition: Are champions being recognized appropriately? Can they see the career benefit?

Key Takeaways

• 
  Champions are force multipliers. One well-supported champion can drive adoption across a whole team or function better than formal training.
• 
  Select champions carefully. Look for respected peers, pragmatists, and people who are open to change, not necessarily the most technical people.
• 
  Recruit, don't mandate. Champions work best when they volunteer. Make an offer, explain the time and support, and respect if they decline.
• 
  Protect their time. 20% of their work week in the first quarter is not negotiable. If you can't free them from other work, don't make them champions.
• 
  Invest in support. Early training, direct access to experts, peer networks, and regular check-ins make the difference between champions who thrive and those who struggle.
• 
  Recognize visibly. Public recognition, career credit, and potential financial compensation show champions they matter. Without it, they'll stop advocating.
• 
  Evolve the role. As adoption spreads, champions transition from launch advocates to deep specialists to mentors. Keep them engaged by evolving their role.
• 
  Build a peer network. Champions connected to each other are more effective than isolated champions. Regular roundtables, peer learning, and shared challenges strengthen the network.