In speedskating, tenths of a second can determine whether an athlete wins gold or misses out on medals entirely.

To hunt for those slivers of a second, the U.S. Olympic speedskating team has put traditional analytics on ice and turned to a new tool powered by artificial intelligence to simulate skaters’ complex aerodynamics.

The new app, called Slippery Fish and custom designed for the team, is one of an emerging suite of AI-powered tools U.S. Olympic teams use to improve athletes’ performances ahead of the 2026 Milan Cortina Winter Games opening Friday.

Emery Lehman, 29, a member of the speedskating team competing at this year’s Games, said the AI-enabled app has revolutionized how he and the wider team approach training.

“We used to have athletes fly out across the country to a wind tunnel, spending all of this time and money, where they would then stay in a static position so the team could gather aerodynamic data,” Lehman told NBC News last week as he exercised on a stationary bike during the team’s practices in southern Germany.

“With this app, it’s all just done through AI,” said Lehman, an engineer who won a bronze medal at the 2022 Beijing Olympics. “In the team pursuit, for example, we want to maybe make a change and find a position amongst the three guys or girls who are skating so the whole group can be more aerodynamic.”

The Slippery Fish app, based on a similar AI-powered aerodynamic analytics tool for cyclists called AiRO, allows coaches to upload images of an athlete on the ice. From those images, the app creates a digital avatar of the athlete and simulates how different postures affect airflow and drag, variables critical to speedskating success.

“We can now plug changes in posture into this app and see if those tweaks are actually efficient or not,” Lehman said. “Then we can go on the ice, see if it’s practical and kind of evaluate from there. Something that maybe took a week or two to validate or say ‘that was a good or bad idea,’ that can now be done in a day.”

Shane Domer, chief of sport performance for the speedskating team, agreed that the AI-powered technology had improved how the team trains, calling it “a wind tunnel in your pocket.”

“We want to test new positions in short periods of time so we can iterate on the fly, actually have conversations and really get our coaches and athletes involved in the process,” Domer said. “We’re looking at tiny adjustments, like whether skaters’ elbows are drifting out from their body, and examining what kind of time cost is involved.”

AI systems have become increasingly capable over the past year, with new iterations able to analyze troves of data to create insights and provide detailed recommendations based on new research techniques. To harness the growing abilities, the USA bobsled and skeleton team announced a new partnership in November with Snowflake, one of the world’s leading AI-focused data analytics companies.

For Curt Tomasevicz, director of sport performance for the bobsled team, the new collaboration has allowed better understanding of individual athletes’ strengths and weaknesses, enabling coaches to provide better advice and improve overall team performance ahead of the Milan Cortina Games.

“It sounds very simple to load two or four athletes into a sled,” said Tomasevicz, who won the gold medal in the four-man bobsled at the 2010 Vancouver Olympics and has a doctorate in bioengineering. “But when you have four athletes running and you’re asking different athletes to get in at different times before they truly feel like they’re maximizing their push, it goes against their natural tendency sometimes.”