The future of AI in healthcare depends on high-quality real-world data (RWD) to improve patient outcomes and clinical decision-making. This comprehensive guide explores how AI companies must leverage large, linked, and longitudinal datasets - particularly unstructured data sources - to develop robust models, achieve FDA approval, and gain adoption among community physicians. Learn why quality RWD is essential for AI model development, regulatory validation, and real-world implementation, plus discover key examples of successful and failed AI healthcare initiatives based on their data strategies.