“You’re seeing athletes there with full-time coaches,” White told Fortune’s Andrew Nusca at Brainstorm Tech in Aspen this week. “I didn’t have that kind of access.”

But the emergence of new technologies, especially AI, has helped make it easier for athletes to have similar access to important resources to improve performance, even if some don’t have a full-time coaching team. 

“It is leveling the playing field in a way,” White said. “This is really going to be accessible for everyone…It’ll give a lot of information to athletes that wouldn’t have had this type of access before, and that’s really the hope.”

AI has already made it into the world of sports analytics. MLB debuted its Automatic Ball-Strike (ABS) system that allows players to challenge and overturn an umpire’s call at home plate. Similar automated line and boundary calls and Semi-Automated Offside Technology (SAOT) have been implemented in tennis and soccer, respectively. For athletes, AI can pair with wearable biosensors to record movements and suggest improvements to form.

The International Olympics Committee has outlined an AI agenda with the intention of integrating the technology into judging. During the 2026 Milano Cortina Winter Olympics, ski jumpers used high-speed video and motion analysis to dissect their takeoff timing, aerodynamics, and in-run speed. 

While snowboarders, skiers, and skaters of older generations previously enlisted friends or parents to take videos of their runs, AI can now provide nearly real-time feedback with specific metrics to improve performance, according to Granville Valentine, managing director of AI Sales and GTM for Google Cloud in North America, who also spoke at Brainstorm Tech. He said Google’s Gemini can generate world models down to the hundredth of a millimeter and can identify where an athlete’s skeletal structure is, as well as their center of gravity.

“Not only can we collect tremendous amounts of data—all that velocity, speed, rotation, all that useful data for our athletes—but [we’re] making sense of it, collating it, and giving it back as really easy human-level coach ups in between runs in real time,” Valentine said.

Where Shaun White sees the future and limits of AI in sports

White has seen the technology rapidly change over the course of his own career, and it’s helped inform how he sees AI being used for the next generation of athletes. When the 39-year-old began his snowboarding career, the halfpipe in the facilities he used were hand-dug with shovels. Now a large pipe-cutter essentially carves a wall of ice for athletes to use, allowing halfpipes to be larger.

The Olympian has adopted a similar philosophy for how AI can bolster not just performance, but potentially the longevity of one’s career by preventing injuries. While White was coming of age, young athletes attempting a new trick would hope for the best. Today, AI can provide key projections on how a trick could strain someone’s body.

“We were basically rock, paper, scissors, who was going to go first for a big trick?” White said. “This is a potentially—hopefully not career ending—but maybe season-ending trick you’re about to go for. You didn’t really have any information, you just kind of like, saw something that inspired you, you got with your friends, you’re just gonna go try it.”

To be sure, White said, the risk, spontaneity, and human skill are still what makes sports unique. He argued AI had the power to democratize athlete’s access to data on their performance, and can be used by judges to more objectively assess the technical prowess of a competitive run. But at the end of the day, it’s all still about the love of the game.

“We’re not trying to replace the human experience,” he said. “We don’t obviously want to create this sort of analysis paralysis situation where you’re so bogged down in the details that you don’t actually get out there and do the sport.”