Olympic road cycling champion Kristen Faulkner has unlocked a new level of performance, crediting a sophisticated, self-designed AI system for her recent 20-minute power personal best. Over the past two months, Faulkner dedicated more than 10 hours daily to coding and analyzing her personal biometric data, a testament to her innovative approach in a field often lacking dedicated research for elite female athletes. This groundbreaking work has not only optimized her training but also empowered her to take control of her athletic development, bridging a critical gap in sports science.
Faulkner, a professional cyclist with EF Education-Oatly, shared on LinkedIn the extensive work involved in developing her AI system. She integrated various data points such as heart rate, sleep patterns, body weight, power output, and menstrual cycle phases. This comprehensive dataset was then cross-referenced with 4,400 hours of her past training history, allowing the AI to generate highly specific and actionable recommendations tailored to her unique physiology. Her initiative stems from a recognized void in performance research for women, particularly at the elite level, which often leaves female athletes without personalized, data-driven insights.
The cyclist emphasized that existing athletic tracking applications offered only fragmented views of her performance. Despite meticulously collecting biometric data for nine years, including heart rate variability, training load, body temperature, bloodwork, and DEXA scans, she found no single platform capable of synthesizing this diverse information into a cohesive narrative. Frustrated by the limitations of conventional tools and the scarcity of female-centric research, Faulkner embarked on building her own solution. Her background, holding a computer science degree from Harvard University and investing in AI ventures, provided her with the unique expertise to develop this advanced analytical framework.
Faulkner's personalized AI models, specifically trained on her historical data, proved instrumental in her recent triumphs. She credited these insights for contributing to her three gold medals at the Pan American Championships: victories in the individual pursuit, team pursuit on the track, and the road time trial. She recounted moments of intense dedication, often transitioning directly from training rides to coding sessions to process and analyze her latest data. Her journey into professional cycling began at the age of 28, following a successful career in venture capital, and she has consistently approached her sport with an analytical mindset, studying competitors and course details meticulously.
The landscape of AI-powered training platforms has seen significant expansion, with options like HumanGo offering virtual coaching, and apps such as Spoked, Vekta, and Garmin Coach providing AI-driven training plans. Even legendary figures like Sir Bradley Wiggins have embraced AI, with a chatbot version of him available through The Coachsters app. However, experts like David Bailey, head of sport science at NSN Cycling Team, caution against over-reliance on AI, stressing the importance of athletes remaining attuned to their body's natural signals and sensations. While AI offers powerful analytical capabilities, a balanced approach combining technology with intuitive understanding is crucial for holistic athletic development.
Kristen Faulkner's journey highlights a significant shift in elite sports training, where athletes are increasingly leveraging advanced technology to gain a competitive edge. By taking a proactive role in developing her own AI research, Faulkner has not only enhanced her personal performance but also demonstrated the immense potential for AI to personalize and revolutionize training methodologies, especially in under-researched areas of women's sports science.