'AI is going to change women's performance research from the bottom up' - Kristen Faulkner inputs 4,400 hours of personal training history and gains 'actionable' output

Kristen Faulkner, a rising star in women’s cycling and Olympic gold medallist, has taken a pioneering approach to her training by integrating artificial intelligence with her extensive biometric data. Drawing on her computer science background from Harvard, Faulkner developed a personalised AI system that analyses over 4,400 hours of her training history. This innovative tool synthesises diverse data points such as heart rate, sleep patterns, menstrual cycles, and power output to generate actionable insights tailored specifically to her physiology, moving beyond generic dashboards to deliver precise performance optimisation. Faulkner’s motivation stems from a recognised gap in women’s sports science, where research often overlooks the unique needs of elite female athletes. Frustrated by the lack of comprehensive analytics, she dedicated months to coding and refining her AI model, which she credits for immediate performance gains, including three gold medals at the Pan American Championships and a personal best in her 20-minute power output. Her approach represents a shift in how female athletes can harness technology to better understand and enhance their bodies, challenging traditional methods that have largely been male-centric. Her journey is particularly remarkable given her relatively late entry into professional cycling, having previously worked in venture capital and actively investing in AI companies. Faulkner’s methodical preparation—studying competitors, courses, and her own data—has been a key factor in her rapid ascent, including stage wins at the Giro d’Italia Donne and Vuelta España, as well as double Olympic golds in Paris. Looking ahead, she aims to leverage her AI-driven insights to defend her Olympic title at the Los Angeles 2028 Games, underscoring her commitment to combining intellect and innovation in elite sport. Beyond performance metrics, Faulkner is also vocal about broader health issues in cycling, such as the pressures surrounding racing weight and energy management. She advocates for working with the body’s natural rhythms rather than forcing changes, a philosophy she promotes through initiatives like the @f.e.e.d_powr platform. Her work signals a growing movement within women’s cycling to prioritise athlete health and data-driven training, potentially reshaping the sport’s approach to female performance research from the grassroots level upwards.