AI adoption is often presented as a technology challenge. Buy the right tools, provide access and encourage employees to start experimenting.
But for smaller organisations, the reality is more complex. Budgets are limited, priorities compete and employees need more than access to technology before they can confidently change how they work.
At the Engage Employee Summit, Ollie Brenig-Croft, Senior Learning and Culture Manager at Formula E, shared how the organisation is approaching AI adoption in a practical, people-focused way.
His message was clear: successful AI adoption is not just about technology. It is about skills, culture, trust and change management.
Formula E is a global electric racing championship with around 230 employees. Its workforce spans events operations, commercial teams and business functions including HR, finance, legal and technology.
Technology is central to the organisation’s identity, from the electric cars competing around the world to its partnership with Google Cloud. Employees also have access to Google’s Gemini tools and other AI resources.
Yet access alone does not guarantee adoption.
Formula E is a young, fast-moving organisation with ambitious growth plans and many competing priorities. As Ollie explained, it is in something of a “difficult teenager” phase: no longer a start-up, but not yet a mature organisation either.
That creates plenty of opportunities to innovate, but also important questions about how the business should evolve.
The skills required for work are expected to change significantly over the coming years. But giving people access to AI does not automatically change how they work.
Employees need the confidence, capability and support to use new tools effectively. They also need to understand how AI will affect their roles and how it can augment their work rather than simply replace it.
For Formula E, this means focusing on three connected areas:
These factors make AI adoption much more than a training project. It becomes a broader transformation programme involving leadership, culture, processes and employee experience.
Formula E began by creating an AI champions programme.
The aim was simple: identify people who were enthusiastic about AI and give them the opportunity to learn, experiment and support others.
The organisation expected around 10 employees to volunteer. More than 30 came forward — a significant number for a company of just over 200 people.
The programme was built internally and involved basic training, practical experimentation and opportunities for champions to share their experiences. Employees were encouraged to ask questions, celebrate successful use cases and show colleagues what was possible.
The approach was deliberately low-cost. It did not require a large-scale transformation programme or significant external investment. Instead, it created a community around AI and gave interested employees the confidence to become advocates.
Formula E also used fun and informal activities to bring the group together. A visit to Google’s offices included technical training, but also a cooking class designed to build relationships and reinforce an important principle: the people learning the technology are just as important as the technology itself.
The AI champions programme helped encourage individual experimentation. Formula E’s technology teams were also developing more advanced projects using Google Cloud.
But a gap remained between these two areas.
AI was being used by individuals for tasks such as drafting emails, creating content and analysing documents. Meanwhile, technical teams were using it for complex projects connected to data, racing and business operations.
What was missing was the middle layer: the everyday business processes that move between teams, systems and departments.
These workflows often involve several people and stages. They may include sales, sponsorship, commercial operations, finance or internal approvals. They are more complex than an individual task, but may not require a fully technical solution.
Identifying and improving these processes became the next challenge.
Formula E initially considered providing role-specific AI training. However, a senior stakeholder raised a difficult question: do employees need formal AI training when they can simply ask AI how to use it?
The question prompted the organisation to reconsider its approach.
There was a risk that conventional training could quickly become outdated as AI tools changed. There was also the familiar challenge of skills transfer: employees may complete a course but struggle to apply what they have learned in their day-to-day work.
Rather than rushing into training, Formula E stepped back to consider what capabilities employees would need and how those capabilities could be developed in a way that remained relevant.
Formula E is now exploring three connected approaches.
The organisation is trialling a 12-month AI apprenticeship with a group of AI champions.
The focus is on people who understand their roles and business processes but may not come from technical backgrounds. By combining their existing expertise with AI capability, Formula E hopes to develop people who can identify relevant opportunities and apply AI in practical ways.
This approach is designed to keep learning connected to real work rather than treating AI as a purely theoretical subject.
Formula E is also exploring the introduction of an AI change manager.
The role would involve assessing business workflows, identifying pain points and understanding where AI could have the greatest impact. It would also consider how technically demanding each opportunity is and whether it could be delivered by non-technical specialists.
This assessment is an important foundation. Organisations can easily rush into AI projects before fully understanding the problem they are trying to solve.
Mapping processes first helps ensure that investment is directed towards meaningful opportunities rather than interesting technology with limited business value.
The third area is leadership.
Managers will need to help employees navigate uncertainty, experiment safely and adapt as roles evolve. Adaptability and resilience will become increasingly important, particularly as AI tools and expectations continue to change.
Leaders will also need to create clarity around how AI should be used, what is expected of employees and how success will be measured.
Formula E’s approach is not about trying to become the fastest organisation to adopt every new AI tool.
Instead, it is moving quickly while recognising its practical constraints. The organisation is balancing ambition with limited budgets, competing priorities and the need to understand where AI can create genuine value.
That balance is particularly relevant for small and mid-sized organisations. They may not have the resources for large transformation programmes, but they can still make meaningful progress by:
AI may be changing the tools people use, but successful adoption still depends on familiar principles of employee engagement and organisational change.
People need a clear reason to change, opportunities to practise and learn, support from leaders and confidence that the transition will benefit rather than diminish their working lives.
Formula E’s experience demonstrates that organisations do not need unlimited budgets or perfectly defined long-term plans to begin. They need a practical starting point, a willingness to learn and a clear focus on the people who will use the technology.
The most effective AI strategy may not begin with a technology purchase. It may begin with a conversation about how work happens today — and what employees need to do it better tomorrow.
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