Pedagogical objectives

• Identify situations where you unconsciously delegate your judgment to AI
• Develop practical habits to prompt action, analyze responses, and make decisions with a clear head
• Challenge your team's critical thinking regarding their AI deliverables without hindering adoption

The program

Session 1: My Personal Clarity
‍AIgenerates fluid, well-structured, and seemingly solid responses. That is precisely what makes them risky. Participants explore the biases it amplifies (confirmation bias, groupthink) through concrete scenarios, then practice the RAP method: Slow down before prompting (a cognitive pause involving three questions to clarify assumptions before the AI reinforces them), Truly analyze the responses (confidence calibration, contradictory prompts), Take a step back from the entire decision-making process.

Case example : Rewording a biased prompt to test a hypothesis rather than confirm it, and measuring the difference in the quality of the resulting diagnosis

Session 2: My Team’s Work
‍AnAI-generated deliverable can be well-structured and delivered quickly, without any real thought behind it. Participants learn to challenge their colleagues’ deliverables by focusing on the reasoning rather than the result, and to formulate delegations that require them to take a stand.

Case Study : When presented with a generic plan generated by AI, identify what is missing, ask the right questions of the team member, and rephrase the brief to obtain a deliverable grounded in the real-world context

Session 3: My Team’s Cognitive Culture
‍Eachmanager leaves with their own guidelines for AI use within their team: recommended practices, points to consider, and traceability requirements. The goal is to establish a framework that maintains a high standard of critical thinking without hindering adoption.

Example of a tool : the risk zone grid (trust in AI vs. self-confidence, task by task) to identify where to prioritize the activation of critical thinking mechanisms