The CASES resource on Artificial Intelligence

Dr Andy Smith MBE FCASES, Dr Mark G. E. White, Dr Eddie Bradley MCASES, Dr Tim Donovan, Prof Joanne Hudson FCASES, Abdullah Khalid, Dr Sarah Powell MCASES and Dr Clare Strongman

Abstract

This resource equips Sport and Exercise Scientists – whether new to artificial intelligence (AI) or already proficient – with insights and practical guidance to better understand and apply AI effectively.

Links are included to over 20 AI tools relevant to Sport and Exercise Science (SES), offering practical insights into their capabilities, limitations and applications. This work is underpinned by an extensive set of references.

Executive Summary

The current impact of AI on SES is illustrated through material on digital twins, virtual and augmented reality, smart clothes and the ‘Internet of Things’, and markerless motion capture. AI’s potential transformative impact on SES resulting from the development of large language models is explored, emphasising the importance of the human-in-the-loop.

Several AI tools that can be used for research in SES are presented. These fall into four main categories: literature review; data analysis; report writing; and grant acquisition.

AI is reshaping higher education teaching and assessment by generating lessons, scaffolding explanations for diverse learners, creating quizzes, and drafting formative feedback. Academics must shape environments that ensure AI is used ethically and constructively.

Sports-performance AI now delivers real-time analysis of physiology, biomechanics, tactics, and injury risk. Simulated environments and reinforcement-learning ‘next-play’ models safely let coaches test tactics and opponent behaviour. Practitioners must rigorously evaluate these tools to ensure responsible, ethical use that prioritises athlete wellbeing and performance.

The use of wearable technology to monitor and evaluate sport and fitness activity has become ever-present. Using AI and big data appears to have promising applications within health and fitness, but increased consideration of human factors may be needed to develop this technology further.

AI systems in exercise prescription are increasingly integrated into clinical and fitness settings to provide scalable and personalised exercise offerings. Many of these AI systems are rooted in the biomedical model, focusing on measurable outcomes like heart rate. Expanding their design to incorporate recreational, social and nature-based activities such as ‘green’ and ‘blue’ prescriptions might improve their impact on public health.

AI can inform ethical thinking but cannot be relied on to be ethical, fair, or to embody professional values. Ethical decisions remain a human responsibility.

SES faces several challenges if it is to ensure that AI has a positive impact on the profession. These include but are not limited to:

• preparing the next generation of professionals
• establishing what best practice in SES looks like in the use of AI
• preparing for other technological developments that will emerge because of, or alongside, AI.

AI is better than human ignorance but not human reasoning or uniquely human qualities. It is a tool for Sport and Exercise Scientists to improve the human condition, so whilst this resource highlights AI strengths, practitioners should focus on the tasks humans do best.

Keywords

AI