Weight management serves as a critical component in the prevention and control of chronic diseases. In 2024, the National Health Commission of China launched a three-year "Weight Management Year" action plan (2025-2027), aiming to enhance public awareness of weight management and promote scientific control methods. Weight management not only focuses on body weight values but also emphasizes comprehensive interventions in diet, physical activity, and lifestyle to prevent chronic diseases and improve quality of life. Generative artificial intelligence demonstrates significant potential in the field of weight management by providing users with personalized dietary advice, exercise plans, and behavioral interventions, thereby improving management outcomes and adherence. This article systematically explores the application pathways and effectiveness of generative artificial intelligence in weight management, highlighting its advantages in achieving dynamic personalization of dietary plans and increasing physical activity levels, while also addressing multiple challenges such as content authenticity, data privacy, algorithmic biases, and long-term adherence. This study provides valuable insights for the optimization of weight management models in China and the further application of generative artificial intelligence in the health domain.

体重管理是慢性病防控的重要环节。国家卫生健康委员会于2024年启动为期3年的"体重管理年"行动计划（2025—2027年），旨在提升全民体重管理意识并推广科学的体重控制方法。体重管理不仅关注体重数值，更强调通过饮食、运动和生活习惯的综合干预，以预防慢性病、提升生活质量。生成式人工智能在体重管理领域展示出巨大潜力，可为用户提供个性化的饮食建议、运动方案及行为干预，从而提升管理效果与依从性。本文系统探讨生成式人工智能在体重管理中的应用路径与实效，指出其在实现饮食方案动态个性化、提升身体活动水平等方面具有优势，同时也面临内容真实性、隐私安全、算法偏见及长期依从性等多重挑战。本文可为我国体重管理模式的优化与生成式人工智能在健康领域的深入应用提供参考。