by Javier Hernández (ERNI Spain)
Almost every organisation has made AI adoption a strategic priority, providing employees with access to AI tools in the hope of reducing costs and creating more value for customers and the business. AI is no longer a promise. It is already part of our reality, transforming how companies, markets and professionals operate.
Many leaders try to drive AI adoption by giving their teams access to powerful tools and communicating their importance, hoping that these measures will create AI-enabled teams. This generates activity, with employees using AI to correct emails, translate documents or generate content. However, the expected improvements in productivity and efficiency often fail to materialise. Why doesn’t providing access to AI tools automatically lead to meaningful adoption?
At ERNI, we have been exploring this question through our AI Champions initiative, which brings together more than 50 people from different roles, teams and business areas.
Driving adoption through Champions
AI Champions are ERNIans who have voluntarily taken responsibility for driving AI adoption forward and supporting our ambition to become a human-centred, AI-powered company. The initiative currently involves more than 50 AI Champions from different teams, projects and areas, including People, Talent, HR, Sales, Marketing and Technology.
Their purpose goes beyond encouraging people to use AI or building a network of enthusiastic tool users. AI Champions bridge the gap between business needs, employee adoption and measurable business impact. By understanding both how AI is transforming organisations and the day-to-day realities of their teams, AI Champions are well placed to identify opportunities where AI can create value or reduce effort.
They identify promising use cases, test them in a controlled environment, measure the results, and receive support in deciding whether an initiative should be scaled up, improved or discontinued. Our model combines local ownership with central coordination. AI Champions receive support from experts and collaborate across teams, business areas and projects, sharing experiences and identifying new opportunities.
ERNI’s experts provide a baseline in AI literacy and large language model (LLM) fundamentals, alongside practical guidance on using these tools effectively in their daily work. Between sessions, AI Champions put their knowledge into practice by conducting experiments and exploring new use cases. This hands-on approach helps turn theoretical knowledge into practical experience.
What we have learnt from putting AI Champions into practice
Implementing this initiative has not been without challenges. Selecting the right Champions and ensuring representation across areas has proved difficult. Another challenge has been forming groups based not only on interests and roles but also on expertise and knowledge, to encourage stronger collaboration.
Smaller groups foster discussion and learning, but they can also limit interaction across the wider network. Expert support, combined with a lightweight governance model, has been essential in connecting these groups and building a broader community where knowledge, tools and experiments can be shared across the organisation.
This exchange is already taking place. Teams are adopting practices and tools such as SDD and Wiki LLM, while colleagues with stronger technical backgrounds support those in less technical roles with tool configuration, proofs of concept and practical use cases. After our first three months, around 10 experiments connected to specific business needs are already underway. These initiatives cover not only internal processes but also activities related to our customers.
One example comes from Talent Acquisition, where dedicated AI Skills support the creation of job descriptions, candidate profiles, outreach messages and Boolean searches. The aim is to reduce administrative effort, improve consistency and enable recruiters to focus more on candidate engagement and hiring decisions.
The AI Champions initiative is also part of a broader AI governance model covering architecture, security and privacy, platform and technical foundations, access and licensing, as well as local sites and business value.
Five questions every AI experiment should answer
Before scaling up an AI experiment, organisations should be able to answer five key questions:
- What business need are we addressing?
- What will change in the way people work?
- How will we know whether the experiment is delivering value?
- Is the use of AI safe and appropriate in this context?
- If it works, what is needed to scale it? If it doesn’t, what have we learnt?
These questions help organisations move from simply using AI to adopting it meaningfully and, ultimately, achieving measurable impact.
If your organisation has already given employees access to AI but is still struggling to connect usage with tangible business results, ERNI can help. Contact us to explore how an AI Champions initiative and a practical governance model could support your next steps.
