Priorisation des Investissements IA pour les Dirigeants

Ce qu'elle couvre

Ce programme dote les sponsors exécutifs et les comités de pilotage de méthodes structurées pour évaluer les initiatives IA selon leur valeur métier et leur faisabilité technique. Les participants travaillent sur des scénarios de portefeuille réels à l'aide de matrices valeur/faisabilité, de critères de passage de phase et de techniques d'équilibrage de portefeuille. Les sessions combinent de courtes séquences pédagogiques avec des exercices de scoring pratiques appliqués aux initiatives candidates de l'organisation. À l'issue de la formation, les dirigeants sont en mesure d'animer eux-mêmes un comité d'investissement IA sans facilitation externe.

À l'issue, vous saurez

• Design and apply a weighted scoring rubric to rank a portfolio of AI initiatives by value, feasibility, and strategic fit
• Construct a value-vs-feasibility matrix using your organisation's own candidate initiatives and reach a defensible sequencing decision
• Define stage-gate criteria that prevent premature scaling of unproven AI pilots
• Identify portfolio imbalances (e.g. too many moonshots, no quick wins) and rebalance allocation accordingly
• Facilitate an executive AI investment review meeting using a structured agenda and decision log

Sujets abordés

• AI opportunity landscape: hype vs. proven value patterns
• Value-vs-feasibility matrix construction and calibration
• Scoring frameworks: weighted criteria, risk-adjusted ROI, and strategic fit
• Stage-gate design for AI initiatives (discovery → pilot → scale)
• Portfolio balancing: quick wins vs. transformational bets
• Build-buy-partner decision logic for AI capabilities
• Governance checkpoints and executive accountability models
• Communicating AI investment decisions to the board

Modalité

Typically delivered as two full-day in-person sessions or three half-day virtual workshops spread over two to three weeks, allowing participants to complete between-session scoring exercises on live initiatives. Materials include scoring templates (Excel/Notion), a stage-gate playbook, and a portfolio dashboard starter. Hands-on exercises account for roughly 60% of contact time. Remote delivery uses Miro for collaborative matrix work. An optional pre-work survey collects the organisation's candidate initiatives to personalise case studies.

Ce qui fait que ça marche

• Anchoring the scoring criteria to stated business strategy before the first workshop session
• Including both business and technology voices in the scoring panel to avoid blind spots on either side
• Embedding the stage-gate model into existing PMO or board reporting cadences so it is used after the training
• Nominating a single owner for each initiative in the portfolio to maintain accountability through gate reviews

Erreurs fréquentes

• Evaluating AI initiatives purely on cost savings while ignoring strategic optionality and learning value
• Letting vocal champions push high-complexity initiatives to the top without a structured feasibility check
• Treating the scoring framework as a one-time exercise rather than a recurring governance ritual tied to budget cycles
• Confusing a successful proof-of-concept with readiness to scale, leading to premature large-scale commitment

Fournisseurs à considérer

• MIT Sloan Executive Educationexecutive.mit.edu/course/artificial-intelligence-implications-for-business-strategy/ →
• INSEAD Executive Educationwww.insead.edu/executive-education/digital-transformation-innovation/leading-ai →
• McKinsey Academywww.mckinsey.com/capabilities/mckinsey-digital/how-we-help-clients/mckinsey-academy →
• HEC Paris Executive Educationexecutive.hec.edu/program/artificial-intelligence-for-business/ →

Sources

• A Practical Guide to Building Ethical AI — Harvard Business Review →
• The State of AI in 2024 — McKinsey Global Survey →