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Innovation and Technology

Digital Twin Technology and the LA 2028 Olympics Divide

João Guarda

LA28 Olympics, Digital Twin, Google Cloud, Snowflake, Team USA, Olympic AI, Sports Technology, Competitive Fairness, Athlete Data, IOC

28 Apr 2026

Digital Twin Technology and the LA 2028 Olympics Divide
The USA enters the 2028 Games with tech advantages built within the tournament's infrastructure, widening a gap between nations, threatening fair competition.

 

The 2028 Los Angeles Olympics will be the first Summer Games at which digital twin technology is embedded directly into the host nation's athlete preparation infrastructure. Google Cloud and Snowflake have both signed partnerships with the LA28 organising committee and with the United States Olympic and Paralympic Committee, giving American athletes access to advanced AI-powered training tools built on the same platforms that underpin the Games themselves. 

Is the existing Olympic governance framework equipped to address structural conflict of interest?

 

 

 

How Team USA's technology advantage was built

Google Cloud is a founding AI and infrastructure partner for LA28, responsible for key operational systems across the Games. The same company also provides Gemini AI models and cloud infrastructure directly to Team USA athletes through a separate partnership with the US Olympic and Paralympic Committee. 

 

Snowflake, as the official data collaboration provider for both LA28 and Team USA, creates a unified environment where American athletes' training data, health records and nutrition information are integrated in a single platform ahead of the competition.

 

 

The result is that the host nation arrives at the Games with a multi-year head start in AI-supported athlete preparation, built on the same systems that run the tournament itself. Germany, Great Britain and a small number of other wealthy nations have their own independently developed programmes. The overwhelming majority of the 206 national Olympic committees do not.

 

 

 

Why this inequality is harder to fix than previous resource gaps

Wealthy nations have always had better training facilities, nutrition programmes and scientific support than developing ones. The standard response to this has been that a talented athlete with dedication can compensate for resource disadvantage through effort and ability. Digital twin systems change the calculation in a specific way.

 

Building a meaningful digital twin requires minimum thresholds of computing power, data collection equipment and specialist expertise in biology and machine learning. Below those thresholds, the technology does not exist in any useful form. 

 

There is no partial version that a lower-income national committee can deploy at reduced quality. The gap is not a matter of degree, it is a matter of presence or absence. An athlete whose taper before a final was managed by an experienced coach guessing at optimal timing is not at a slight disadvantage to one whose timing was calculated from months of individualised physiological modelling. In some events, the difference may be decisive. 

 

Beyond competition, athletes from nations without predictive injury systems face a higher risk of avoidable career-ending injuries, which is a duty of care for the IOC as the event organiser.

 

 

 

What a fairer framework could look like after LA28

The IOC's current AI policy, introduced in 2024, focuses on fairness in judging, improvements to the spectator experience and operational efficiency. It does not address unequal access to performance technology. Closing that gap would require a deliberate policy decision rather than a commercial one, and the IOC's existing partnerships make neutrality on this question structurally difficult.

 

One path forward involves directing a portion of Olympic commercial revenues into a technology access fund for lower-income national committees, providing baseline digital twin infrastructure rather than attempting to match the most advanced programmes. A parallel step would involve developing open-source baseline models, built on training data from diverse athlete populations, that any national committee could deploy without licensing costs. 

 

FIFA's stated goal of providing equal analytical access to all 48 World Cup nations offers a partial precedent, and the IOC generates considerably more commercial revenue than FIFA. The window for intervention is narrowing. The data relationships, commercial contracts and competitive precedents set at LA28 will be difficult to undo by the time the 2032 Brisbane Games arrive.

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João Guarda

João Guarda

João Guarda is an upcoming writer for Sportsabc and the Ztudium team: primarily focused on sports, João has been contributing to the team since February 2025. Despite specializing in sports, João has a wide range of knowledge from literature, art, history to politics and economics.

Born in Leiria, Portugal; João lived in Paris, France for a major part of his life, mastering both the English language as well as the French and Portuguese Language.
He is currently studying Communications at Lisbon University and desires to become a proficient actor in the field.

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