How Team USA’s Olympic Skiers and Snowboarders Got an Edge From Google AI

The American team’s skiers and snowboarders are heading home with new equipment, including a few gold medals, 2026 Olympic Games. In addition to the years of hard work it takes to become an Olympic athlete, this year’s crew received an added advantage in their training thanks to a custom AI tool from Google Cloud.

US Ski and Snowboard, the governing body of America’s national teams, oversees the training of the nation’s best skiers and snowboarders to prepare them for major events, such as national championships and the Olympics. The organization partnered with Google Cloud to create an AI tool to offer more insights into how athletes train and perform on the slopes.

Video review is an integral part of winter sports training. A coach will literally stand on the sidelines to record an athlete’s run, then later review the footage with them to spot mistakes. But that process is somewhat outdated, Anouk Patty, head of sports at US Ski and Snowboard, told me. That’s where Google came in, bringing new AI-driven insights to the training process.

Google Cloud engineers are hitting the slopes with skiers and snowboarders to understand how to create an AI model that’s actually useful for sports training. They used video footage as the basis for the currently unnamed AI tool. Gemini performed a frame-by-frame analysis of the video, which was then fed into Google DeepMind’s spatial intelligence models. These models were able to take the 2D rendering of the athlete from the video and turn it into a 3D skeleton of an athlete as he contorts and twists during the race.

Gemini’s finishing touches help the AI ​​tool analyze pixel physics, according to Ravi Rajamani, global lead of Google’s AI Blackbelt team. who worked on the project. Coaches and athletes told engineers the specific metrics they wanted to track (speed, rotation, trajectory) and Google engineers coded the model to make it easier to monitor and compare between different videos. There is also a chat interface to ask Gemini questions about performance.

“From a simple video we are able to recreate it in 3D, so you don’t need expensive equipment, [like] sensors, which hinder an athlete’s performance,” Rajamani said.

Coaches are undeniably the experts on the mountain, but the AI ​​can act as a sort of instinctive control. Data can help confirm or refute what coaches see and give them additional insight into the specifics of each athlete’s performance. It can capture things that humans would have difficulty seeing with the naked eye or with poor video quality, such as where an athlete was looking while performing a spin, as well as the exact speed and angle of a spin.

“This is data they wouldn’t have otherwise,” Patty said. The 3D skeleton is particularly useful because it makes it easier to see movements obscured by the puffy jackets and pants athletes wear, she said.

For elite ski and snowboard athletes, making small adjustments can mean the difference between a gold medal or no medal at all. Advancements in training technology aim to help athletes have all the tools available to improve.

“You’re always trying to find that 1% that can make the difference for an athlete to get on the podium or win,” Patty said. It can also democratize coaching. “It’s a way for every coach that works at a club and works with young athletes to have that level of understanding of what an athlete should do that national team athletes have.”

For Google, this purpose-built AI tool is “the tip of the iceberg,” Rajamani said. There are many potential future use cases, including expanding the base model to customize it for other sports. It also lays the foundation for work in sports medicine, physiotherapy, robotics and ergonomics, disciplines in which understanding body position is important. But for now, we’re happy knowing that AI was designed to actually help real athletes.

“It wasn’t about technology engineers building something in the lab and handing it over,” Rajamani said. “This is a real problem that we are solving. For us, the motivation was to create a tool that provides a real competitive advantage to our athletes.”