Application of artificial intelligence for developing personalized training programs in Ukraine

Abstract

The relevance of the study is driven by the growing demand for increased efficiency in physical activity through digital technologies and the urgent need to adapt training programs to users' characteristics. In the context of digital transformation in health and sports, the application of artificial intelligence for analyzing physiological and behavioral data presents new opportunities for personalizing the training process and integrating intelligent solutions into the fitness industry and sports medicine. The study aims to scientifically justify the potential use of artificial intelligence in developing personalized training programs, taking into account users' biomechanical, physiological, and behavioral characteristics, as well as to define the directions for effective implementation of such technologies in wellness and sports practice in Ukraine. The methodology is based on structural-functional analysis of AI-powered training systems, comparative assessment of international best practices, modeling of adaptive load algorithms, and systematization of current challenges and solutions related to the digital transformation of the training process. The results reflect the current state of AI-based personalized training systems and their implementation. Mechanisms of load adaptation to individual user parameters have been analyzed; global and Ukrainian case studies are presented, including the WOD Insight startup. Significant challenges have been identified, such as limited access to advanced technologies, lack of high-quality training data, low digital competence among professionals, and the absence of regulatory frameworks. Conclusions confirm the need to develop a national digital platform for personalized training, establish a regulatory standard, and introduce interdisciplinary educational programs in AI and physical culture. The importance of a comprehensive approach to the digital transformation of health and fitness practices is emphasized. Prospects for further research include the development of ethical models for managing personal data, testing the effectiveness of adaptive training programs across target groups, and creating integrated solutions using cloud technologies in sports and rehabilitation.