Formula One teams generate and analyze data at a scale most enterprises would struggle to manage, yet the people leading that work argue the sport’s competitive edge still belongs to experienced humans. Aston Martin Aramco’s technology leadership, speaking around a tour of the team’s Silverstone campus ahead of the British Grand Prix, made the case that handcraft and professional judgment are what turn raw data into racing performance.
The team’s technical partners frame the sport as an extreme test bed for AI. A modern Formula One car contains more than 13,000 components, with new parts designed on average every 15 minutes during the development cycle, and engineers must weigh aerodynamic variables, environmental conditions, and race strategy under extreme time pressure. Machine learning has been used for years to analyze car data and identify performance signals, and the team now mixes generative and agentic AI into the workflow to develop proactive responses to challenging scenarios.
CIO Fabrizio Pilotti describes IT as a performance-enhancing function rather than a support operation. The department’s job, in his telling, is to give engineers the data foundations and tools that let them make the most of their abilities, through better management of faults and a clearer understanding of how the car performs. Priority projects include refining enterprise applications, developing trackside systems, and applying AI agents tactically to the software development process itself.
The striking detail from the campus visit was the coexistence of cutting-edge AI with traditional craft. Adrian Newey, the team’s managing technical partner and one of the most celebrated aerodynamicists in the sport’s history, was drawing new designs by hand in his office. Pilotti said new joiners are often surprised by how much detailed handcraft the work involves, and that in a marginal-gain business, small tailored modifications by specialists are exactly the kind of increment that decides races.
The human role persists because AI in this setting is treated as a decision-support layer, not a decision-maker. The engineer with years of experience is the one who looks at several options generated from data and picks the path, using judgment that models do not possess. Eric Ernst, the team’s commercial technology ambassador, framed this in terms of cognitive scalability: AI gives the team’s people the capacity to do more than they can today, but the experience itself cannot be outsourced to a model.
The partner ecosystem reflects that philosophy. Cohere, which works with the team on sovereign AI models and agents, is exploring how models can draw timely insights across telemetry, diagnostics, and simulation data, automating the mundane work that slows engineers down. Pilotti said the team wants to deploy models for tailored use cases that run within the firewall, keeping sensitive data contained and token usage in check. Arm supplies energy-efficient compute that supports faster decision cycles in high-stakes situations like pit stops, and Cognition is working on AI agents that act as extensions of the engineering team, breaking down complex problems and learning on the job.
The data infrastructure underneath all of it has itself become a competitive question. The team announced in October 2025 that it had completed moving its data storage entirely onto NetApp, and it named CoreWeave its AI cloud computing partner in May 2025, though the team guards the details of where specific workloads run, citing competitive sensitivity. Blocks & Files reported in July that the team owns its own GPUs and that much of its data processing remains on-premises, with CoreWeave running AI models on that hardware.
The broader message from the team’s technology forum was aimed beyond racing. Formula One, in this telling, stress-tests AI under conditions no enterprise can replicate: extreme time pressure, safety-critical decisions, and data that cannot be exposed. The skills that matter in that environment, the argument runs, transfer directly to other industries. The race to integrate AI into operations is extending into data centers and software platforms, but the finish line still depends on the people interpreting what the models produce.
Sources: AI in Formula One: Competitive advantage is all about the human in the loop (ZDNet, Aug 1, 2026); Aston Martin Formula One: Accelerating Innovation with AI (Manufacturing & Engineering Magazine, Jul 29, 2026); Aston Martin’s Aramco Formula One Team, CoreWeave, NetApp, and the race to gain a competitive storage advantage (Blocks & Files, Jul 13, 2026); Aston Martin Aramco Formula One Team Now Fully Powered by NetApp Storage (Business Wire, Oct 8, 2025)