The Future Role of Artificial Intelligence in Exercise and Health Sciences

Abstract

Artificial intelligence (AI) is rapidly transforming numerous fields within 

medicine and health science, and exercise and health sciences are no exception. 

From automated movement analysis and wearable sensor integration to predictive 

modelling of injury risk and personalized exercise prescription, AI technologies 

offer unprecedented opportunities to enhance the precision, efficiency, and 

scalability of health-related research and clinical practice. This perspective 

article examines the current landscape of AI applications in exercise science, 

sports medicine, rehabilitation, and public health, and discusses the 

methodological, ethical, and practical challenges that accompany their 

integration. Key areas addressed include machine learning approaches to 

performance optimization, AI-assisted diagnostic tools in sports injury 

assessment, the use of natural language processing in health behavior research, 

and the implications of algorithmic decision-making for patient-centered care. 

The article also considers the limitations of current AI systems, including 

issues of data quality, model transparency, and generalizability across 

populations. We argue that the responsible integration of AI into exercise and 

health sciences requires interdisciplinary collaboration, robust ethical 

frameworks, and a sustained commitment to research transparency and equity. 

This perspective aims to provide researchers and clinicians with a foundational 

overview of AI's evolving role in the field and to stimulate critical discussion 

about its future directions.