How to start AI training in your company: a 5-step plan

Many companies want their team to learn to work with artificial intelligence but do not know where to start. The most common mistake is to start from the tool: buy licences and hope people figure it out. That almost never happens. AI training pays off only when it starts from concrete work. Here is a 5-step plan for how to begin.

Where NOT to start

Do not start with "which tool should we pick". Start with "which of our tasks take the most time and repeat". A tool without a concrete task becomes one more open browser tab that everyone forgets within a week.

Step 1: pick 2–3 real tasks

Find work the team does often and that takes time: preparing proposals, writing emails, summarising reports, sorting customer requests. Starting from two or three clear tasks beats trying to "apply AI everywhere". Once people see the benefit in one task, they start looking for more uses themselves.

Step 2: assess the team's level

One team needs an introduction and confidence; another is ready for advanced techniques. Before training, it helps to talk to people and learn who has already tried AI and who has never opened ChatGPT. Training matched to the real level delivers far more than one identical course for everyone.

Step 3: learn with your own data, not with examples

This is the biggest difference between an open course and in-company training. A generic course shows how to write a poem or generate an image. A team needs something else – how to prepare your proposal, summarise your report, answer your customers' questions. When you learn with real work tasks, people continue where they left off after the training instead of starting from scratch.

Step 4: agree on the rules

Before using AI more widely, it helps to agree on simple rules: what data can go into the tools and what cannot; when an answer must be checked; who is responsible for the final result. This is not bureaucracy but protection against mistakes and data leaks. Clear boundaries give people the confidence to use the tools every day.

Step 5: measure the result

Decide what counts as success: time saved on a task, a faster reply to a customer, less manual work. You do not need a complex system – just ask the team how long the same work takes before and after the training. Without measurement, training stays "that was interesting"; with it, it becomes an investment you can repeat.

How long does it take?

Teams usually see first results right after the training because they work on their own tasks. Habits change more slowly – for AI to become part of daily work, it takes a few weeks of practice and often a follow-up session to discuss what worked and where people got stuck.

How we help

We run AI training for companies and teams on exactly this principle: we start from your work, learn with your data, and, if needed, extend the training into real implementation. We are practitioners who deploy AI in real projects, not just talk about it.

If funding is on your mind, see how the competence voucher works for AI training. And if you want to start with a specific team, read what AI training looks like for a sales team. Questions? Get in touch – we'll look at what fits your team.