How to grow AI knowledge across your organisation

Start by asking questions

Before deciding what employees need to learn, you need to understand where they are today.

How are they already using AI? What do they feel confident doing? What do they avoid? What makes them curious or concerned? And, perhaps most importantly, what problems are they trying to solve in their everyday work?

If employees cannot see how AI can help them in their own role, training that focuses mainly on features and functionality is unlikely to make much difference.

Not everyone needs to become an AI expert

Different departments and roles need different levels and types of AI knowledge. There should be a shared foundation: an understanding of the opportunities and limitations of AI, security considerations and the organisation’s rules for using AI. From there, learning can become more role-specific.

Instead of asking, “Have you completed the AI training?”, ask: “What do you need to know to use AI effectively in your work?”

Leaders also have an important role to play. A leader who feels uncertain about AI will find it difficult to help their team navigate change, experiment with new ways of working and build confidence.

Let your next AI training session start with a real task

Imagine two training sessions.

In the first, employees are shown a long list of features in an AI tool.

In the second, they bring a real task from their working week. They use AI to tackle it, review the result, adjust their instructions and try again.

The second approach makes AI relevant immediately.

Using AI is a skill, and skills develop through practice. The first attempt may even take longer than doing the task without AI. That does not necessarily mean AI has no value. It may simply mean you are still learning when to use it and how to use it well.

Make it easy to do the right thing

Employees need clear boundaries for using AI. Which tools are approved? What information can be shared? What should you do when you are unsure? Who can you ask?

An AI policy only becomes useful when it is translated into everyday working practices. Employees need to understand not only what the rules are, but also why they exist. The goal should not be to make people afraid of using AI. It should be to make it easier to use AI safely and effectively.

Your best AI teacher might be sitting a few desks away

Useful AI knowledge often develops in different parts of the organisation at the same time. Someone discovers a use case that saves time every week. Someone else finds a prompt that consistently produces better results. Another person learns, through trial and error, when AI is simply the wrong tool for the job.

Create opportunities for employees to share those experiences. That could mean AI ambassadors, recurring forums or a shared space where employees can exchange use cases, prompts, questions and lessons learned.

AI knowledge grows through training, but it also grows between employees.

And when the training is over?

The work continues! AI tools are changing quickly, and so are the ways we use them. Building AI competence therefore cannot be treated as a one-off initiative. Follow up on more than course completion. Look at how AI is actually being used, where it creates value, what is not working and where employees still feel uncertain.

The goal is not to tick off an AI training course and avoid another reminder email. The goal is to create a learning organisation where employees can continue to explore, build and develop their AI knowledge as part of everyday work.