AI training for leaders often falls into one of two traps. Too technical, it leaves the executive committee with vocabulary but no reference points for deciding. Too general, it leaves them with promises, but nothing concrete to apply the following Monday.
Our conviction: in a well-designed half day, an executive committee can acquire the essentials it needs to steer its AI topics. Provided you choose what to teach, and what to leave out.
What a leader really needs to know
What AI does well, and what it does badly
Classifying, forecasting, summarizing, generating, spotting anomalies: AI excels at repetitive, well-defined tasks for which data exists. It remains fragile when faced with the unexpected, implicit context and unprecedented decisions. Knowing where that line lies avoids most badly started projects.
How to recognize a good use case
A good use case brings together three things: a quantified business problem, available data and a team ready to change the way it works. It is also small enough to deliver within a few months. A leader who knows how to apply this filter can sort in one hour a list of ideas that would otherwise have taken a quarter.
What questions to ask their teams and suppliers
- What problem does this project solve, and how will the result be measured?
- What data does it rely on, and who owns it?
- What happens when the system gets it wrong?
- Who will maintain it a year from now?
What they can ignore
The inner workings of models, detailed comparisons of the tools of the moment, the jargon that changes every six months. These topics matter for technical teams. For leadership, they distract from what determines success: the choice of problems, the resources allocated and governance.
A leader doesn’t need to know how to build a model. They need to know when to say yes, when to say no, and on what conditions.
How the half day unfolds
- Understand. What AI is today, its capabilities and its limits, illustrated with cases from your sector.
- Demystify. The most costly misconceptions, and the real risks: data, ethics, vendor dependency, regulation.
- Identify. A workshop on your own activities to identify and rank your first use cases.
- Decide. Next steps, owners and success criteria, agreed before leaving the room.
The committee leaves with a short list of prioritized use cases, a shared vocabulary and a method to assess the projects that will be presented to it next. This is the purpose of our AI Literacy program, in its format dedicated to leadership teams.
What teaching taught us
Teaching AI in engineering schools, like training teams in companies, teaches a valuable discipline: explaining simply without oversimplifying. A leader deserves the same rigor as an engineering student, with a different goal: not to build systems, but to decide which ones to build.
Let’s organize this half day with your executive committee.
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