Artificial intelligence transforms professional cycling technology

Professional cycling is undergoing a technological transformation driven by data analysis, digital metrics, and artificial intelligence. By 2026, teams and riders are expected to rely heavily on large volumes of information—including power, cadence, speed, heart rate, and energy consumption—to make real-time race decisions, adjust training loads, and prevent injury or overtraining.

However, this technological shift presents significant ethical and regulatory challenges. The ability of AI to rapidly design new drugs, as demonstrated by biotech firm Insilico Medicine with the development of Rentosertib, raises concerns about the emergence of undetectable performance-enhancing substances.

Furthermore, the concept of “digital twins”—virtual models that simulate an athlete's specific characteristics—could allow for unprecedented personalization of training and performance. Experts warn that this same technology could be misused to create highly customized, undetectable doping regimens tailored to an individual's unique physiological data.