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Racing legend and F1 commentator Graham Duxbury takes a closer look at Artificial Intelligence in F1: the hidden driver.
Behind the advanced aerodynamic shapes and mouldings that characterise Formula One cars in the current ground-effect, hybrid-powertrain era lies a less visible but unquestionably formidable and transformative force:
Today, Artificial Intelligence (AI) has an increasingly powerful impact when it comes to on-track performance and off-track operations. It acts, along with machine learning (ML), as a silent collaborator in design, engineering, race strategy, car development and much more.
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Data Driven
At the heart of AI’s influence in F1 are immense volumes of data. A single car generates gigabytes of telemetry per race weekend. Teams capture everything from suspension travel, steering inputs and brake application patterns to acceleration rates, tyre degradation profiles and aerodynamic pressure differentials.
“Data goes into every decision we make,” says Hannah Schmitz, strategy engineer at Red Bull Racing. She explains that even before a team arrives at the track, simulations already predict how tyres will behave relative to surface temperature, grip levels and a host of environmental variables.
Click here to read why its so much more difficult to race a MotoGP bike than it is to drive an F1 car.
AI Simulations
What’s more, overtaking opportunities, pit stop timing and race-start positioning are modelled through AI-powered simulators that replicate real race conditions. Once the lights go out, these same algorithms continuously analyse thousands of live data points. These are compared with predicted models to refine strategy in real time.
Only recently, machine-learning (ML) algorithms were trained primarily on historical datasets to uncover patterns, predict outcomes and support human decision-making. Now, with big-data companies partnering with most teams to provide real-time analytics, the sport has entered a new, forward-looking era.
Predctive, not Reactive
ML is no longer a simple aid for the strategists – it actively drives strategy. This is helping teams mitigate risk, optimise performance and seize competitive advantages measured in milliseconds. ML systems flag anomalies, detect early signs of component failure and suggest optimal adjustments to engine settings or aerodynamic balance long before small issues become race-ending problems.
In short, the reactive is being replaced by the predictive. And while the cars remain in focus for race fans, the unseen web of sensors, processors and AI tools behind the scenes is quietly reshaping the future of F1.
A New Revolution
As a result, AI is revolutionising car design and development. Computational Fluid Dynamics (CFD) models, once reliant on traditional supercomputing, are now accelerated with ML-driven solvers. These evaluate thousands of micro-variations in bodywork and airflow interactions. This shortens simulation times while enhancing accuracy and reducing design cycles.
AI systems now help correlate simulated and on-track results more effectively by integrating real-time track data with wind-tunnel testing. Similarly, predictive maintenance algorithms forecast component wear ensuring maximum reliability.
Driver Ananlysis
Even driver performance sits under AI’s analytical microscope. Telemetry analytics benchmark every input. Throttle, brake, steering is analyzed lap-by-lap and areas where marginal gains can be found are highlighted.
Dan Keyworth, McLaren’s director of business technology, describes the team’s approach as “turning data into speed”. ML models simulate thousands of scenarios, providing probability-based insights to guide decision-making. “Some of our predictions have become almost scary in their accuracy,” he admits.
McLaren uses “digital twins” – detailed 3D virtual replicas of their F1 cars. This allows engineers to model the effects of setup changes in real time, translating virtual performance into on-track results. Aston Martin has developed what the team calls ‘vast data lakes’ – massive central repositories – to analyse tyre data, weather patterns, track evolution and many other variables to predict likely race outcomes.
No Human Replacement
“The speed at which these developments are happening is really impressive,” says Clare Lansley, Aston Martin’s CIO. She notes that AI and ML have freed engineers to focus on performance improvements rather than “number crunching”.
Could AI one day replace the strategists, engineers and even team principals on the pit wall? “No,” says Lansley firmly. “On the contrary, AI allows the heavy lifting to be done by the machine, enabling experienced engineers to make more informed decisions – the kind that can mean the difference between first and second.”
She adds that AI will not replace expertise but will redefine it. “In departments like aerodynamics, engineers are now being cross-trained in AI so they can use these tools to turbocharge their work.”
F1 has always been a sport where technology and skills meet in a high-speed contest. It’s going to be interesting to see how AI will help perfect the technology and improve the quality of F1’s innate talent pool.
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