Train your staff to check what AI actually produces
In brief
Journal du Net argues that AI answers look confident even when they are wrong, which leads people to copy them without checking. According to the article, most AI training covers models and prompts, not critical reading of the output. It sets out practical habits and cases where systematic checks are needed, including numbers, legal references and anything that leaves the company.
Source : Journal du Net - « Apprendre à douter de l'IA : cinq réflexes à transmettre aux salariés »
What it changes for an SME
For an SME, an unchecked AI mistake in a figure, a client email or a legal reference can waste time and damage trust. If you train people to ask for sources, to test the tool on topics they know, and to keep the final decision human, you lower that risk without heavy tools. The article also says personal or confidential data should be checked before it is given to an AI system. If questioning an AI answer is seen as slowing work down, staff will stop doing it, so your managers need to treat it as part of the job.
What you can do
- Write a one-page list of documents that always need a check and who is accountable for each type.
- Have staff practise on real AI answers that contain errors from their own work, so checking becomes a habit.
- Always verify numbers, legal or contractual references, and any text that leaves the company.
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