Frame the use case before you pick an AI model
In brief
According to LeMagIT, choosing a model is a core decision at the start of an AI project, whether you use a cloud offering, compare vendors or an open-weight model. The same constraints apply: reliable output, cost control and data protection. The article sets out a five-step method, from framing the use case to governing later changes.
Source : LeMagIT - « Choisir et gouverner ses modèles d’IA : une méthode en cinq étapes »
What it changes for an SME
For an SME of 10 to 250 people, the sequence of work changes: you first define what the system may do, the quality and response time you accept, and when a person must take over, with agreement from the business, security and operations. According to LeMagIT, you should start with suppliers already under contract, and leave that perimeter only if a real gap or a measured benefit covers the extra contract, security and integration cost. Self-hosting, according to the article, must be costed as a full service, including skills and peak capacity. The article also notes that an open-weight model, European hosting and control over the operator are not the same thing.
What you can do
- Before any trial, get business, security and operations to approve what the system may do, the quality you require and when a human takes over.
- Check with your existing suppliers where data and logs go, how long they are kept and whether they can be reused.
- Build a set of real examples, including unclear and high-impact cases, and keep a separate set to judge results without using it to tune instructions.
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