Licences give access. Habits create value.
What a short AI pilot taught us about adoption, everyday work and why technology alone is rarely enough.
Access is only the beginning
Many AI projects begin in the same place: with technology, access and licences. That is a natural starting point. But it is also where the real work begins.
In a recent pilot with a large organisation, a limited number of Microsoft Copilot licences were distributed to employees and leaders as part of a test period. The goal was simple: to understand whether the tool could create enough value to justify a broader investment.
But the organisation also recognised something important from the beginning: handing out licences would not be enough. If people were going to change how they worked, they needed more than access. They needed relevance, rhythm and support.
Why AI adoption is different
AI may be new technology, but adopting it is not quite like learning a new system. With many digital tools, the challenge is to understand where to click and how the process works. With AI, the challenge is more behavioural. It is about building new habits into existing workflows.
A generic training session on what AI can do rarely creates lasting change on its own. It becomes useful when people can see how it applies to their own tasks, meetings, documents, priorities and decisions. This is also why adoption guidance increasingly points to communities, champions and ongoing learning as important parts of building momentum.
Train for intention, not just interfaces
One important learning came early in the training. It became clear that not everyone’s Copilot or AI tools looked the same. Some people had access to one version, others to another, and the interfaces kept changing.
That means AI training cannot only be about where to click. It has to start with the intention: What are you trying to achieve? What task are you working on? And how can AI help you move forward?
Start small, make it practical
To support the pilot, we designed a short and focused learning format: 30-minute sessions built around everyday use. The ambition was not to explain everything AI can do. It was to help people start using it in ways that felt concrete and manageable.
The sessions were built around three simple principles:
Start small: build AI into existing workflows instead of treating it as something separate.
Create habits: use it regularly enough for it to become part of the working rhythm.
Build on what you learn: begin with familiar tasks, then gradually try more advanced uses.
The quiet users matter too
Alongside the sessions, we helped build activity around an internal community channel. This was not just about sharing tips. It was about creating a space where people could ask questions, see examples and learn from each other.
When you work with AI adoption, it is often the most engaged users you hear from first. They post in the channel, join the conversation and try new things quickly. But they rarely represent the whole organisation.
That is why it was important to create activities that also made space for the quieter users: the people who were still figuring out where AI could help, what good use looked like, and how to bring it into their everyday work.
Want to turn AI access into everyday value?
If you are exploring how to move from AI licences to real adoption, get in touch with Britt McCarthy Mors at bmo@weareopen.eu to hear more about how we help organisations build the habits, confidence and everyday use cases that make AI create value in practice.