ai-champion-network-builder

name: ai-champion-network-builder description: Use when building grassroots AI adoption. Use during AI program scaling. Produces champion identification, enablement program, and community structure.

AI Champion Network Builder

Overview

Build a network of AI advocates across business units to drive grassroots AI adoption. Identify, enable, and support champions who accelerate AI adoption in their domains.

Core principle: Peer influence drives adoption. Champions bridge central AI teams and business units to accelerate value realization.

When to Use

• Scaling AI adoption beyond early adopters
• Building sustainable AI culture
• Enabling decentralized AI innovation
• Reducing bottleneck on central AI team

Output Format

champion_network:
  program_name: "[Name]"
  launch_date: "[YYYY-MM-DD]"
  
  program_design:
    purpose: "[Why building network]"
    scope: "[Organization coverage]"
    target_size: "[How many champions]"
    
  champion_profile:
    characteristics:
      - "[Trait 1]"
      - "[Trait 2]"
    
    time_commitment: "[Hours per week/month]"
    
    responsibilities:
      - "[Responsibility 1]"
      - "[Responsibility 2]"
    
    not_responsible_for:
      - "[Clarify what they don't do]"
  
  identification:
    sources:
      - "[How to find candidates]"
    selection_criteria:
      - criterion: "[Criterion]"
        weight: "[Importance]"
    
    nomination_process: "[How nominated]"
    approval: "[Who approves]"
  
  enablement:
    onboarding:
      - "[Training/resource 1]"
    
    ongoing:
      - "[Ongoing support 1]"
    
    tools_access:
      - "[What champions get access to]"
  
  structure:
    reporting: "[Relationship to AI team]"
    community:
      meetings: "[Frequency and format]"
      communication: "[Channels]"
      collaboration: "[How they work together]"
  
  recognition:
    program: "[How champions are recognized]"
    incentives: "[Any formal incentives]"
  
  metrics:
    program_health:
      - "[Metric 1]"
    impact:
      - "[Metric 1]"
  
  champions:
    - name: "[Name]"
      business_unit: "[BU]"
      domain: "[Focus area]"
      joined: "[Date]"
      status: "[Active | Inactive]"

Champion Profile

Ideal Characteristics

Champion Responsibilities

responsibilities:
  evangelize:
    - "Share AI success stories"
    - "Demystify AI for colleagues"
    - "Address concerns and resistance"
  
  identify:
    - "Surface AI use cases in their area"
    - "Connect use case owners with AI team"
    - "Assess feasibility with domain knowledge"
  
  enable:
    - "Help colleagues adopt AI tools"
    - "Provide peer support"
    - "Gather and relay feedback"
  
  advise:
    - "Represent business unit perspective"
    - "Inform AI team of domain needs"
    - "Shape AI strategy and priorities"

Not Responsible For

boundaries:
  - "Building AI solutions (that's AI team's job)"
  - "Formal AI training (coordinate with L&D)"
  - "Technical support (escalate to AI team)"
  - "Approval of AI projects (follow governance)"

Identification Process

Finding Champions

sources:
  nominations:
    - "Manager nominations"
    - "Self-nominations"
    - "Peer recommendations"
  
  signals:
    - "Early adopters of new tools"
    - "Active in learning programs"
    - "Asking questions about AI"
    - "Already helping colleagues"
  
  coverage:
    - "At least one per major business unit"
    - "Mix of roles and levels"
    - "Geographic distribution if relevant"

Selection Criteria

selection:
  must_have:
    - "Manager support for time commitment"
    - "Domain expertise"
    - "Communication skills"
  
  nice_to_have:
    - "Technical aptitude"
    - "Prior change agent experience"
    - "Formal influence (but not required)"

Enablement Program

Onboarding

onboarding:
  orientation:
    duration: "Half day"
    content:
      - "Program overview and expectations"
      - "AI strategy and roadmap"
      - "Available tools and resources"
      - "Community introduction"
  
  training:
    - "AI literacy (if needed)"
    - "Prompt engineering basics"
    - "Use case identification"
    - "Change management fundamentals"
  
  early_wins:
    - "Quick task to apply learning"
    - "Identify first use case in their area"

Ongoing Support

ongoing:
  community:
    - "Monthly champion meetup"
    - "Shared communication channel"
    - "Peer mentoring pairs"
  
  resources:
    - "Champion toolkit (templates, guides)"
    - "Early access to new tools/capabilities"
    - "Direct line to AI team"
  
  development:
    - "Advanced training opportunities"
    - "Conference attendance"
    - "Leadership visibility"

Measuring Success

Program Health Metrics

health_metrics:
  engagement:
    - "Active champions / Total champions"
    - "Meeting attendance rate"
    - "Channel activity"
  
  retention:
    - "Champion tenure"
    - "Departure reasons"

Impact Metrics

impact_metrics:
  adoption:
    - "AI tool adoption in champion areas vs. non-champion"
    - "Use cases surfaced by champions"
    - "Use cases advanced to production"
  
  enablement:
    - "Colleagues supported by champions"
    - "Training referrals"
    - "Support queries deflected from AI team"

Checklist

• Champion profile defined
• Identification sources mapped
• Selection criteria set
• Enablement program designed
• Community structure planned
• Recognition program defined
• Success metrics established
• Executive sponsorship secured