What is an AI Champions Program?
An AI Champions program is an internal train-the-trainer initiative that creates a network of AI advocates within your organisation. Rather than relying solely on external trainers or a central IT team, AI Champions become the go-to resource for their departments — answering questions, sharing best practices, and driving adoption from within.
This model is proven across industries and geographies. It scales AI adoption far more effectively than top-down mandates or one-time training events.
Why AI Champions Work Better Than Central IT
| Approach | Advantage | Limitation |
|---|---|---|
| Central IT team | Technical expertise | Limited understanding of business context |
| External trainers | Professional delivery | Leave after the workshop, no ongoing support |
| AI Champions | Know the department, speak the language, always available | Need initial investment in training |
AI Champions bridge the gap between technical AI knowledge and business context. They understand their department's workflows, challenges, and culture — which means they can translate AI capabilities into practical applications that their colleagues will actually adopt.
How to Build an AI Champions Program
Step 1: Define the Program Structure
Before selecting champions, define the program:
- Program name: Choose something that sounds aspirational but not gimmicky (e.g. "AI Champions", "AI Ambassadors", "AI Leads")
- Time commitment: Typically 10-15% of their working time (4-6 hours per week)
- Duration: Initial intensive training (2-3 days), then ongoing role for 6-12 months
- Reporting line: Champions report to their existing manager but have a dotted line to the AI governance committee
- Recognition: How will champions be recognised? (Certification, performance review credit, title, etc.)
Step 2: Select Your Champions
Selection Criteria
Not every enthusiastic employee makes a good AI Champion. Look for:
- Influence: Respected by peers, good communicator, natural leader
- Curiosity: Genuinely interested in AI, willing to experiment and learn
- Business acumen: Understands their department's workflows and pain points
- Reliability: Follows through on commitments, meets deadlines
- Diversity: Represent different departments, levels, and backgrounds
How Many Champions?
| Company Size | Recommended Champions |
|---|---|
| 10-50 employees | 2-3 |
| 50-200 employees | 5-8 |
| 200-500 employees | 10-15 |
| 500+ employees | 1 per 30-50 employees |
Selection Process
- Nominations — Invite self-nominations and manager nominations
- Applications — Short application form: why they want to be a champion, their department's AI opportunities, and their availability
- Interviews — Brief conversation with the AI governance lead to assess fit
- Confirmation — Selected champions receive a formal appointment letter and their manager is notified of the time commitment
Step 3: Train the Champions
Champion Training Curriculum (2-3 days intensive)
Day 1: Advanced AI Skills
- Deep prompt engineering (chain-of-thought, few-shot, role-based)
- Advanced use of approved AI tools
- Evaluating AI output quality and accuracy
- Troubleshooting common AI tool issues
Day 2: Governance and Risk
- Company AI policy deep dive
- Data privacy and PDPA compliance
- AI risk assessment process
- Incident identification and reporting
- Handling employee questions about AI ethics
Day 3: Teaching and Advocacy
- How to deliver informal training sessions
- Creating department-specific use cases and prompts
- Change management techniques for AI adoption
- Handling resistance and fear
- Measuring and reporting adoption progress
Ongoing Champion Development
After the initial training, champions need continued support:
- Monthly champion meetings — Share experiences, discuss challenges, learn from each other
- Quarterly skill updates — Training on new tools, techniques, and policy changes
- Access to resources — Prompt libraries, templates, and external learning materials
- Direct line to IT/governance — Fast escalation for technical issues and policy questions
Step 4: Deploy Champions
Champion Responsibilities
Each AI Champion is responsible for:
- Department AI training — Conducting informal training sessions (lunch-and-learns, desk-side coaching, team meetings)
- Use case development — Identifying and prototyping AI applications for their department
- First-line support — Answering questions about AI tools, prompts, and policies
- Adoption tracking — Monitoring and reporting AI usage in their department
- Feedback collection — Gathering user feedback and reporting to the governance committee
- Policy compliance — Ensuring their department follows the AI acceptable use policy
Champion Activity Calendar (Monthly)
| Activity | Frequency | Time |
|---|---|---|
| Department training/demo | 1-2 per month | 1 hour each |
| Champion team meeting | Monthly | 1 hour |
| Use case development | Ongoing | 2-3 hours/week |
| Ad-hoc support | As needed | 1-2 hours/week |
| Progress reporting | Monthly | 30 minutes |
Step 5: Measure and Iterate
Champion Program KPIs
| Metric | Target | Measurement |
|---|---|---|
| Department AI adoption rate | 60%+ using AI weekly | Tool usage analytics + survey |
| Training sessions delivered | 2+ per champion per month | Activity log |
| Use cases developed | 3+ per champion per quarter | Use case register |
| Employee satisfaction with AI support | 4.0/5.0+ | Quarterly survey |
| AI incidents in champion departments | Below company average | Incident log |
| Champion retention | 80%+ stay in programme | Programme records |
Funding the Program
Direct Costs
- Champion training (2-3 days): Claimable under HRDF (Malaysia) or SSG (Singapore)
- AI tool licences for champions: Often included in enterprise licence
- Champion recognition/rewards: Modest budget for certificates, events, etc.
Opportunity Cost
- 10-15% of each champion's time redirected to AI activities
- This is the primary "cost" and should be agreed with department managers upfront
ROI
- Companies with AI champion programmes typically see 2-3x higher AI adoption rates
- The productivity gains from widespread AI adoption far exceed the champion time investment
- Champions often develop into future technology leaders, benefiting their career development
Common Mistakes
- Selecting champions based on seniority rather than suitability — Choose the right people, not the most senior
- Under-investing in champion training — Champions need deeper training than regular employees
- Not protecting champion time — If managers do not honour the time commitment, the programme fails
- Ignoring champion burnout — Monitor workload and provide support; rotate champions if needed
- Not recognising champion contributions — People need to feel valued for their extra effort
Related Reading
- AI Adoption Roadmap — The 90-day plan that your champions programme supports
- AI Training for Managers — Train your champions with management-level AI skills
- Copilot Adoption Playbook — Apply the champions model to Microsoft Copilot rollout
Frequently Asked Questions
A general guideline is 1 AI Champion per 30-50 employees. Small companies (10-50 staff) need 2-3 champions. Mid-size companies (50-200) need 5-8. Larger organisations need 10-15 or more, with at least one champion in every department.
Good AI Champions are respected by peers, genuinely curious about AI, understand their department workflows, reliable in following through, and good communicators. Technical background is helpful but not required — business acumen and interpersonal skills matter more.
AI Champions typically spend 10-15% of their working time on AI activities — roughly 4-6 hours per week. This includes running training sessions, developing use cases, providing support, and attending champion meetings. The initial intensive training takes 2-3 full days.