As technology accelerates, nutrition professionals are increasingly surrounded by AI tools, predictive models, and digital platforms. Yet one truth remains: clients don't change because an app tells them to. They change because a human understands them. Drawing on insights from MIT Sloan's AI in Business Strategy program and nearly two decades of clinical and coaching experience, this session examines where emerging technologies help and where they fall short in capturing human complexity. While machine-learning systems detect patterns, they often miss deeper nuances such as motivation barriers, cognitive load, social determinants, emotional factors, intention-behavior gaps, inaccurate self-reporting, and the clinical red flags dietitians recognize instinctively.

Through compelling real-world stories, case studies, and systems-level analysis, we will explore the future-ready skills RDNs need in an AI-enhanced world. Attendees will learn how to interpret digital inputs from AI coaching tools, wearable recovery metrics, and predictive nutrition algorithms, and how to communicate these limitations within interprofessional teams. This session provides objective analysis and does not endorse any specific products.

Participants will leave with a practical, ethically grounded framework for blending high-tech insights with high-touch relationship-building to deliver more personalized, context-aware care.