Athletes and Sports Competitors

In contrast, most on-field tasks remain human. There’s no robot attending practice sessions or giving interviews – athletes still have to train, compete, and interact with fans and media. Technologies like virtual-reality simulators are being tested for practice, which can let players work on decision skills in a safe setting ^[4].

But even the Olympic organizers say AI should help identify talent and personalize training while leaving final decisions to people ^[1]. In short, today’s AI tools support athletes (for example by predicting injuries or analyzing games) but do not do the core physical work of playing or coaching ^{[1] [1]}.

However, most people tasks in sports still rely on humans and are not bought by AI. Athletes hone skills, handle equipment, and meet fans with human hands and voices. Small college or community teams, with fewer resources, are slower to adopt expensive tech than big leagues.

Socially, players and coaches generally welcome AI for safety and improvement, as long as it doesn’t replace them. For example, the IOC plans to use AI for fair judging and training advice, but stresses it will not “solely dictate” athletes’ careers ^[1]. In summary, AI moves quickly where it adds value (like data analysis and injury prevention) but human skills – practice, teamwork, creativity, and leadership – remain key in sports ^{[3] [1]}.