Xavier McKeever and his cross-country ski teammates once experimented with ChatGPT to create a training plan. The 22-year-old skier from Canmore, Alta., described it as ‘the craziest training plan we’ve ever seen.’ It suggested intense sessions every day, including three hours of skiing followed by an hour of high-intensity work, repeated multiple times, then a full week off. ‘We know you can’t do that,’ McKeever noted. ‘It was pretty funny to see that ChatGPT can’t write a training plan, and that we need our coaches to help us with that.’
AI Emerges as Key Training Tool
Artificial intelligence now plays a significant role in the preparation of Canadian athletes competing at the Milan-Cortina Winter Games in Italy. Machine learning powers devices like Apple and Garmin watches, Oura rings, and inertial measurement units that track sleep, heart rates, and three-dimensional body positioning to deliver recovery scores and performance insights.
Andy Van Neutegem, vice-president of performance sciences, research, and innovation at Own the Podium, Canada’s high-performance sport funding body, clarifies that experts prefer the term ‘machine learning’ over the often-misunderstood ‘artificial intelligence.’ Canadian athletes view AI primarily as a training aid, balancing it with instinct and real-world experience.
Freestyle skier and triple Olympic moguls medallist Mikael Kingsbury emphasizes the need for intuition in his sport. ‘Performance on demand requires some data, but a very good feel for the snow,’ he said. ‘In a sport where things change a lot because we’re outside, I don’t want numbers to be my indicator.’
Advanced AI Applications in Preparation
Sport science remains a closely guarded aspect of Olympic and Paralympic preparation. Certain disciplines, such as snowboarding and freestyle skiing, heavily utilize AI for biomechanical analysis. Van Neutegem explains that computer vision—a branch of AI—mimics human observation to assess optimal body shapes and positioning.
‘The computer detects, does object recognition, and determines whether that’s optimal,’ Van Neutegem stated. In sliding sports, local positioning systems combined with AI identify the fastest lines down tracks by processing vast amounts of historical data.
AI’s Role in Judging and Competition
The International Olympic Committee’s AI Agenda, launched nearly two years ago, highlights its potential to transform judging and refereeing. IOC president Thomas Bach noted, ‘AI can revolutionize judging and refereeing.’
The International Gymnastics Federation tested an AI judging platform at the Paris 2024 Summer Games to assist human judges. Snowboard judging drew scrutiny at Beijing 2022, where Canada’s slopestyle champion Max Parrot admitted touching his knee instead of grabbing his board—a detail judges overlooked.
The X Games has commercialized AI judging through ‘The Owl AI,’ first trialed on men’s halfpipe snowboarders at the 2025 Aspen event. Canadian freestyle halfpipe skier Rachel Karker recalls its use to verify tricks. ‘Everyone does their tricks slightly differently, spinning on different axes with variations,’ she said. ‘It might struggle with nuances, but it’s starting to get introduced in competition. I’m torn on whether it’ll make it better or worse.’
