Learning Objectives
By the end of this lesson, you will understand how to identify potential AI champions within your organisation, recognise the skills and behaviours that make them effective, and learn strategies to empower these individuals as agents of change and innovation in your AI journey.
- Identify Potential Champions: Seek employees who show curiosity for AI, have collaborative mindsets, and demonstrate leadership qualities, regardless of their formal position.
- Assess Skills and Attitude: Evaluate candidates for technical knowledge, communication skills, and openness to learning and experimentation.
- Provide Training and Resources: Offer access to AI learning programmes, mentorship, and hands-on project opportunities.
- Empower through Collaboration: Involve champions in cross-departmental teams to increase visibility and encourage the sharing of success stories and best practices.
- Recognise and Reward Contribution: Publicly acknowledge achievements and provide incentives to maintain motivation and momentum.
- Continual Support and Feedback: Create feedback loops to ensure ongoing development and adapt strategies to organisational needs.
Developing Internal AI Champions Overview
Artificial Intelligence (AI) is transforming industries and redefining how organisations operate, but successful adoption depends not just on technology, but on people. To truly harness the potential of AI, organisations must cultivate a network of internal advocates who can lead, inspire, and drive adoption throughout the business.
These individuals, known as AI champions, play a pivotal role in bridging the gap between technical teams and wider business functions. They help create enthusiasm for AI-powered initiatives, encourage creative problem-solving, and demonstrate hands-on leadership as your organisation navigates the evolving AI landscape.
Commonly Used Terms
Here are some key terms you’ll encounter when developing internal AI champions, explained simply:
- AI Champion: An employee who actively promotes and leads AI adoption, serving as a role model and facilitator for change.
- Stakeholder: Anyone affected by, or interested in, the outcome of an AI initiative—this can include employees, managers, customers, or partners.
- Cross-functional Team: A group made up of members from various departments, brought together to tackle AI projects from diverse perspectives.
- Empowerment: Providing employees with the authority, resources, and support necessary to take initiative and implement new ideas.
- Adoption: The process through which new technology, such as AI, becomes accepted and routinely used within an organisation.
Q&A
How do I spot an AI champion within my team?
Look for individuals who are naturally curious about new technologies, enjoy solving problems, and are willing to collaborate with others. These team members may already advocate for digital tools or volunteer for innovation projects. They don’t have to be technical experts—soft skills like communication and adaptability are just as important.
Can non-technical employees become AI champions?
Absolutely. While technical skills can help, some of the most effective AI champions come from business or operational backgrounds. Their understanding of pain points, workflows and business objectives allows them to bridge the gap between AI solutions and real-world needs.
How can we ensure our AI champions remain engaged and effective?
Provide ongoing mentorship, learning opportunities, and recognition for their contributions. Involve them in meaningful projects, solicit their feedback on AI strategy, and foster a network among champions so they can learn from each other’s experiences and stay motivated.
Case Study Example
Case Study: Empowering AI Champions at a UK Retail Bank
A leading UK retail bank recognised the strategic importance of AI but struggled with staff apprehension and fragmented adoption. To address this, the bank launched an internal initiative to identify and nurture AI champions within each department, rather than relying solely on external consultants or the IT team. They provided targeted training, access to AI tools, and dedicated forums for sharing ideas and obstacles.
One notable AI champion emerged from the customer service team. She lacked formal data science training but possessed a deep understanding of customer pain points and a passion for innovation. With support from management and peers, she co-led a pilot project to implement a natural language processing tool for managing customer queries. Her advocacy built trust in the technology, improved the team’s engagement, and resulted in demonstrable efficiency gains—ultimately inspiring other teams to follow her lead.
Key Takeaways
- Identifying and developing internal AI champions helps bridge technical and business functions for more successful AI integration.
- Effective AI champions demonstrate leadership, communication, initiative, and a willingness to learn and experiment.
- Empowering AI champions requires training, recognition, and continuous support from leadership.
- AI champions foster a culture of innovation and contribute significantly to organisation-wide adoption of AI technologies.
- A strategic, people-first approach is equally as important as technical expertise in ensuring long-term AI success.
Reflection Question
How can you identify and support potential AI champions in your own organisation, and what steps could you take to empower them to drive meaningful change?
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