Many companies buy ChatGPT or Copilot licenses, organize a one-off training course, and six months later find that no one uses them anymore. The problem is almost never the tool: it's the training. Without a structured path, skills on the’artificial intelligence they evaporate quickly and the investment remains on paper.
The good news is that the AI training in companies It's no longer an optional extra or a one-time cost: done well, it's what transforms a tool into a competitive advantage. And starting in 2025, it's also a legal requirement. Let's look at why it matters, what mistakes cause it to fail, and how to build a path that stands the test of time.
Index
- Why AI training has become mandatory
- Mistakes that cause training to vanish
- How to Build a Path That Lasts: 5 Steps
- What AI skills are really needed?
- How to know if it worked
- In summary
Why AI training has become a must (and an opportunity)
From 2 February 2025, the’AI Act European (art. 4) introduces the obligation to artificial intelligence literacyAnyone who develops or uses AI systems must ensure that their staff has an adequate level of expertise. This isn't a bureaucratic detail: it means that training the team on AI is now part of the standard, not an afterthought. If you want a complete overview of the obligations, you can find it in our guide on AI Act obligations for companies.
Beyond the norm, training is what separates companies that have “tried AI” from those that are actually working on it. A tool without skills is just a subscription you pay for.
Mistakes that cause training to vanish
- The “one-off” course. A day in class with no follow-up: after two weeks it's already forgotten.
- Too much theory, too little practice. Explaining what an LLM is is pointless: what's needed is for AI to be tested on real-world work tasks.
- Equal training for all. Those who write offers and those who manage the warehouse have different needs.
- No data rules. Without guidelines, people use AI covertly and riskily.
How to Build a Path That Lasts: 5 Steps
- Start with the tasks, not the tools. Identify repetitive tasks in each department and use them as a training ground.
- Form homogeneous groups. Marketing, administration and production with their own examples, not generic ones.
- Alternate classroom and guided practice. Short sessions followed by real-world exercises, with a contact person to ask.
- Provide clear data rules. A simple policy on what can and cannot be fed to AI.
- Create continuity. Regular updates and a small internal community that shares prompts and results.
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What AI skills does your team really need?
You don't need data scientists. You need practical, transversal skills: knowing how to write clear instructions ("prompts"), recognizing when AI makes mistakes or invents, understanding which data can and cannot be used, and integrating the tool into your workflow. It's a natural extension of the discussion on“artificial intelligence for SMEs: a few right skills, well distributed, are worth more than a single isolated expert.
How to understand if the training has worked
The real metric is not “how many people took the course”, but how many activities are done better or faster Thanks to AI. Keep an eye on concrete signs: time saved on recurring tasks, number of people using the tools each week, quality of output. If after two months, usage has increased and stabilized, the training has taken hold.
In summary
Training your team on AI isn't a one-and-done course: it's a journey of practice, clear rules, and consistency. Start with real-world tasks, form groups, provide data guidelines, and measure actual use. This way, the skills are retained and the investment in AI truly begins to pay off.
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The information contained in this article is for informational and educational purposes only. It does not constitute legal advice and does not replace the advice of a professional. The law is constantly evolving, and its application may vary depending on the specific case. Before making any decisions, always check the latest official sources and, for your specific situation, consult a lawyer or qualified advisor. BigFive assumes no responsibility for decisions based on this information.
