FORMATION IA
L'IA pour les DAF — Transformation de la Finance
Donnez aux directeurs financiers les clés pour déployer l'IA en FP&A, prévision et achats avec crédibilité au comité.
Ce qu'elle couvre
Ce programme offre aux DAF et directeurs financiers une base structurée pour évaluer, piloter et gouverner les initiatives IA au sein de la fonction finance. Les participants explorent des cas d'usage concrets en prévision financière, détection d'anomalies, automatisation du FP&A et intelligence achats, à travers des études de cas issus d'organisations comparables. Le format allie sessions animées par des experts, échanges entre pairs et analyses de scénarios pratiques, pour repartir avec une feuille de route IA concrète pour leur équipe finance. Aucune compétence technique n'est requise — l'accent est mis sur le jugement stratégique, l'évaluation des fournisseurs et l'adoption responsable de l'IA.
À l'issue, vous saurez
- Identify and prioritise the top three AI use cases with measurable ROI for your specific finance function
- Evaluate AI vendor proposals for FP&A and forecasting tools using a structured scoring framework
- Design a governance model for AI-generated financial outputs that satisfies audit and board requirements
- Brief your board or executive committee on an AI finance initiative, including risk, cost, and timeline
- Diagnose data quality gaps that would block a successful AI deployment in finance
Sujets abordés
- AI landscape for finance: what's proven vs. hype in 2024
- Automated financial forecasting and scenario modelling
- Anomaly detection for fraud, reconciliation, and controls
- FP&A automation: from month-end close to rolling forecasts
- Procurement intelligence and spend analytics with AI
- Board-level AI reporting: communicating risk and ROI
- Vendor evaluation and build-vs-buy decisions for finance AI
- AI governance, data quality, and compliance in finance
Modalité
Typically delivered as a blended programme over 3-4 weeks: two full-day in-person or virtual workshops bookended by async pre-reading and a post-session peer accountability call. In-house cohorts benefit from a customised case study drawn from the organisation's own finance processes. Hands-on ratio is approximately 40% applied exercises (vendor scorecard, roadmap canvas, board slide critique) and 60% expert-led content and peer discussion. Materials include a Finance AI Opportunity Canvas, a vendor evaluation rubric, and a board briefing template.
Ce qui fait que ça marche
- CFO personally sponsors a visible quick-win pilot (e.g., automated variance commentary) within 90 days of training
- Finance and IT co-own a shared data quality standard before any AI model is trained
- AI outputs are positioned as decision-support, not replacement, reducing analyst resistance and improving adoption
- Board reporting on AI initiatives is standardised early, building stakeholder trust and securing continued investment
Erreurs fréquentes
- Delegating AI strategy entirely to IT or data teams without finance leadership owning the business case
- Piloting AI on clean, historical data and being surprised when live data quality derails production models
- Underestimating change management: FP&A analysts resist AI tools that feel like a threat to their role
- Selecting vendors based on demos rather than a rigorous evaluation of data integration and auditability
Quand NE PAS suivre cette formation
This programme is not the right fit for a finance team that has not yet standardised its core ERP and reporting data — if the organisation is still reconciling spreadsheets manually, foundational data infrastructure work must come first before AI adoption will deliver value.
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.