The convergence of artificial intelligence (AI) and nutritional science has sparked a new era in healthcare and food technology, giving rise to personalized nutrition systems that adapt dietary recommendations to individual biological, behavioral, and environmental contexts. Unlike traditional one-size-fits-all dietary guidelines, AI-powered personalized nutrition integrates data from genomics, microbiomics, wearable sensors, and lifestyle patterns to offer real-time, individualized dietary insights. This paper explores the architecture, innovations, benefits, and ethical implications of AI-driven personalized nutrition. It reviews current systems such as Viome and Nutrigenomix, highlights challenges such as data privacy and model bias, and outlines future directions including real-time adaptation, emotional nutrition, and AI integration with digital therapeutics. The findings suggest that, while personalized nutrition holds transformative potential for preventive health and food industry innovation, robust ethical frameworks and inclusive designs are critical for equitable and safe adoption.