In this talk, we introduce a systematic approach to AI-driven business solutions by integrating causal reasoning throughout the system design process. Drawing on Aristotle’s Four Causes, NASA’s Technology Readiness Levels (TRLs), and Judea Pearl’s causal modeling, we present a powerful framework for Causal System Design. Through a real-world hospital demand forecasting case, we’ll demonstrate how understanding the root causes of business challenges—beyond data and predictions—unleashes the full potential of AI. Attendees will discover how causal insights enhance decision-making, streamline operations, and align AI systems with business goals, driving transformative impact and lasting value.