Understand through change

You discover what AI can do by putting it to work. A team tries a different way to prepare a proposal, meeting or brief, then sees what saves time and what still needs attention.

Change becomes clearer through practice

An initial result reveals needs you could not fully anticipate: missing data, an implicit rule or a quality criterion known only to an expert. The task is to make these explicit so the next use case improves.

Reuse creates value for the team

A good method becomes more valuable when another colleague can use it. Passing it on means preserving its context and accepting that it will evolve in new situations. Shared expertise then becomes a working foundation, rather than an archive consulted only occasionally.

The rules need to evolve too

As usage expands, information and responsibilities change. Model choices, data masking and alerts help adapt the framework. Adoption and value indicators help ask the right questions about what is worth continuing.

Reference: Thomas Durand, Savoir, savoir-faire et savoir-être.