Formula 1 driver Alex Albon has partnered with the AI and data-products platform Domo to showcase the role of data in racing performance.

This collaboration highlights the critical intersection of human intuition and machine intelligence in high-stakes sports. By leveraging real-time analytics, the partnership demonstrates how technology can bridge the gap between a driver's physical sensations and the car's actual mechanical behavior.

The partnership was formally announced on Nov. 20, 2025 [1]. According to the announcement, the goal is to show how data from a Formula 1 car can be used as a safety net for performance success [1]. This approach is designed to assist drivers who may not be able to feel every nuance of the car's behavior while driving at extreme speeds [2].

In a video produced by Newsmakers, the focus remains on the ability of data analytics to identify performance gaps that are invisible to the human senses [2]. The integration of Domo's platform allows for the visualization of complex telemetry, turning raw numbers into actionable insights for the driver and the engineering team.

By using these data products, Albon and his team can verify whether a driver's perception of the car matches the telemetry recorded by the onboard sensors [1]. This process reduces the reliance on guesswork, and allows for more precise adjustments to the car's setup during a race weekend.

The initiative emphasizes that while the driver remains the primary operator of the vehicle, data serves as an essential verification tool. This synergy between the athlete and the AI platform aims to maximize efficiency and safety on the track [1, 2].

“Data from a Formula 1 car can be used as a safety net for performance success.”

The partnership reflects a broader trend in professional sports where the 'human element' is no longer viewed in isolation but as one part of a data-driven feedback loop. By treating data as a safety net, Albon and Domo are illustrating how AI can augment human skill to reach the theoretical limit of a machine's performance.