El Mostafa Bouattane

The first wave of AI in healthcare was defined by experimentation and proof-of-concept pilots. Today, we’re entering a new era — AI 2.0 — where the focus shifts from isolated innovation to sustainable, integrated clinical tools that enhance outcomes, reduce burden, and scale impact. Take back to your organization strategies to:

• Identify high-impact use cases where AI can be sustainably embedded in clinical settings
• Transition from pilot projects to enterprise-scale implementation
• Align AI development with clinical governance, safety, and usability standard AND Integrate AI tools into EHRs and care pathways to reduce friction and enhance adoption
• Overcome pilot fatigue, ensure clinical buy-in, and achieve measurable improvements.

Realizing the promise of AI — not as a future vision, but as a practical engine for improved patient care today.

Hôpital Montfort began its data transformation with a clear-eyed assessment of its current state: fragmented governance, limited scalability, and inconsistent data literacy. To address these gaps, Montfort designed a strategic roadmap anchored by a robust governance framework, phased policy development, and technology modernization. Develop a road map to:

• Establish a centralized data governance model, defining clear roles and responsibilities, and implementing a Microsoft Fabric Lakehouse architecture for scalable, real-time analytics.
• Optimize an AI-ready, compliant, and agile data ecosystem—enabling advanced analytics, responsible AI deployment, and continuous innovation across the organization.