FORMATION IA
Communiquer l'IA aux parties prenantes non techniques
Les leaders techniques acquièrent les outils pour traduire leurs travaux IA en décisions concrètes pour les dirigeants.
Ce qu'elle couvre
Cet atelier donne aux data scientists et responsables techniques des cadres de communication structurés pour présenter des modèles IA, des résultats et des limites à des publics non techniques. Les participants s'entraînent à expliquer le comportement des modèles sans jargon, à construire des récits autour de l'incertitude et du risque, et à concevoir des visuels adaptés à la prise de décision des dirigeants. Les sessions combinent apports théoriques, critique de démos en direct, jeux de rôle et boucles de feedback. À l'issue de la formation, les participants peuvent animer une revue de projet IA ou un briefing au comité de direction.
À l'issue, vous saurez
- Translate a model evaluation report into a 5-minute executive briefing with clear business implications
- Design a visualisation that communicates prediction confidence and error rates to a non-statistical audience
- Deliver a live AI demo that remains coherent and trustworthy even when the model behaves unexpectedly
- Navigate a difficult stakeholder conversation about model limitations or project setbacks without losing credibility
- Produce a one-page AI project summary that aligns on success metrics with a business sponsor
Sujets abordés
- Structuring an AI narrative for a non-technical audience
- Explaining model mechanics, accuracy, and uncertainty without jargon
- Visualisation patterns that communicate model outputs clearly
- Demo craft: live model demos that build trust, not confusion
- Handling bad-news conversations (model failure, bias findings, scope changes)
- Translating technical KPIs into business impact metrics
- Managing stakeholder questions and objections in real time
- Designing one-pagers and slide decks for AI project reviews
Modalité
Typically delivered as a one- or two-day in-person or virtual workshop. The ratio is approximately 30% instruction to 70% practice: participants bring a real project or are given a realistic case study. Live demo critique sessions require participants to prepare a short (5-10 min) presentation of an AI output beforehand. Materials include a communication framework card, visualisation pattern library, and a stakeholder question bank. Remote delivery works well with breakout rooms for role-play; in-person is preferred for the demo feedback rounds.
Ce qui fait que ça marche
- Practising with real project material rather than abstract case studies, so frameworks transfer immediately
- Having a peer review loop where colleagues critique communication choices before stakeholder meetings
- Establishing a shared vocabulary between technical and business teams prior to formal reviews
- Designating a communication owner on each AI project team to maintain consistency across updates
Erreurs fréquentes
- Leading with model architecture or technical metrics instead of the business question being answered
- Presenting a demo in a controlled environment that collapses under live stakeholder questions
- Using accuracy or F1 scores as headline numbers without contextualising what they mean for real decisions
- Avoiding difficult trade-off conversations (false positives vs. false negatives) until they become crises
Quand NE PAS suivre cette formation
This training is not the right fit when the core problem is that the AI project itself lacks a clear business objective — better stakeholder communication will not compensate for a model that was not scoped around a real decision.
Fournisseurs à considérer
Sources
Cette formation fait partie d'un catalogue Data & IA construit pour les leaders sérieux sur l'exécution. Lancez le diagnostic gratuit pour voir quelles formations sont prioritaires pour votre équipe.