Abstract Objective The integration of artificial intelligence (AI) into healthcare is reshaping clinical practice, administrative workflows, and patient engagement. In obesity medicine, where global prevalence continues to rise, AI offers a scalable and adaptive solution to a complex, chronic disease. This review explores the evolving role of AI, particularly machine learning and generative AI technologies such as large language models (LLMs), AI-enabled behavioral coaching (AIBC), and precision medicine in advancing personalization, scalability and real-time engagement in obesity care. Design Narrative review synthesizing current and emerging applications of AI across clinical, behavioral, and operational domains, with emphasis on emerging technologies and future directions. Methods A comprehensive literature review was conducted using PubMed and leading medical journals. Studies were selected based on relevance to AI applications in patient education, behavioral interventions, precision medicine, and regulatory oversight in obesity care. Results AI driven platforms enable personalized coaching, improving metabolic outcomes, and reducing provider burden through automation and decision support. Generative AI enhances education, remote monitoring and patient engagement. Early trials of AI-enabled behavioral coaching demonstrate proof of concept for clinically meaningful body weight loss and metabolic improvements. Integrating wearables, EHRs, and genomic data with AI tools can create an ecosystem that dynamically supports individualized obesity management. However, challenges remain in clinical validation, accuracy, algorithmic bias and ethical oversight. Conclusion AI offers scalable, adaptive, and patient-centered solutions that complement provider care and improve access to obesity care. Responsible implementation, supported by real-world validation and ethical frameworks, is essential to establish AI as a new standard in obesity care.
Hallock et al. (Mon,) studied this question.