FORMATION IA
Cadre de Décision Make-vs-Buy pour l'IA
Repartez avec un cadre réutilisable pour décider en toute confiance quand développer, configurer ou acheter des capacités IA.
Ce qu'elle couvre
Ce programme dote les responsables technologiques et de transformation d'un cadre structuré pour évaluer les options de sourcing IA — développement sur mesure, configuration d'un éditeur ou achat d'une solution prête à l'emploi. Les participants travaillent sur des études de cas réels couvrant la modélisation du coût total de possession, l'évaluation de l'adéquation stratégique et le profilage des risques pour chaque voie. Le format combine des ateliers animés avec des exercices pratiques sur tableur TCO et des comparaisons entre pairs. À l'issue de la formation, les équipes sont en mesure d'appliquer une méthodologie cohérente et défendable à toute décision d'investissement IA.
À l'issue, vous saurez
- Apply a structured decision matrix to classify any AI initiative as build, configure, or buy within your organisation's context
- Build a defensible TCO model comparing custom AI development against SaaS vendor and open-source alternatives over a 3-year horizon
- Identify the strategic differentiation threshold above which custom AI development is justified
- Assess vendor lock-in risk, data portability, and integration complexity for a shortlisted AI vendor
- Produce a sourcing recommendation document with risk register that can be presented to a board or investment committee
Sujets abordés
- Build vs configure vs buy decision matrix
- Total cost of ownership (TCO) modelling for AI
- Strategic fit and competitive differentiation analysis
- Vendor evaluation and due diligence for AI products
- Risk profiling: data dependency, lock-in, and scalability
- Integration complexity and internal capability assessment
- Governance and compliance constraints on sourcing choices
- Roadmap sequencing and reversibility planning
Modalité
Typically delivered over two to three days in-person or across four live virtual half-day sessions. Approximately 60% of time is hands-on: participants bring one real AI initiative and work it through the framework during sessions. Materials include a pre-built TCO model template, a decision matrix scorecard, and a vendor due diligence checklist. A facilitated peer-review session allows cross-organisation benchmarking. Remote delivery uses Miro for collaborative framework workshops and shared spreadsheet environments.
Ce qui fait que ça marche
- Anchoring the decision in a clearly articulated competitive differentiation thesis before evaluating options
- Using a shared TCO model that finance, engineering, and procurement all co-own
- Building a lightweight governance gate that requires a sourcing rationale document for any AI spend above a defined threshold
- Scheduling a structured re-evaluation trigger (e.g., 18-month review) for every major sourcing decision made
Erreurs fréquentes
- Defaulting to custom build because it feels more strategic, without modelling the true long-term maintenance and talent costs
- Evaluating vendors on feature lists alone, ignoring data residency, model transparency, and exit clauses
- Treating the sourcing decision as a one-time event rather than a revisable position as the AI market evolves
- Excluding legal, security, and compliance stakeholders from the decision, leading to late-stage blockers
Quand NE PAS suivre cette formation
This training is not the right fit for organisations that have already committed budget and signed a vendor contract — at that stage, adoption and change management support is more valuable than a sourcing framework.
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.