In Formula One, the difference between victory and defeat is often measured in fractions of a second. Behind that narrow margin lies a vast operation that depends on data, technology, and above all, people who know how to interpret and act on information under extreme pressure. While much of the public conversation around artificial intelligence focuses on machines replacing human workers, the reality inside an F1 team is quite different: experienced professionals are becoming more important, not less, as AI tools become more sophisticated.
Across the paddock, teams are exploring how generative AI, agentic systems, and advanced analytics can improve car performance, race strategy, and operational efficiency. Yet according to executives at Aston Martin Aramco F1, the most successful digital transformations share a common thread: they are guided by seasoned engineers, strategists, and IT leaders who understand the sport's complexity and the value of human judgment.
Human Expertise at the Center of the Loop
Fabrizio Pilotti, CIO at Aston Martin Aramco F1, says the team's approach to technology is rooted in a simple principle: the idea is only as good as the speed with which it can be tested and refined. "If an idea is good, go through the process as fast as possible, and then get all the data back for the next iteration," he said. "This is where you win, and this is what we're focusing on."
Pilotti describes IT as a performance-enhancing function. The department's role is not to build the car itself, but to give engineers, aerodynamicists, and race strategists the digital foundations they need to do their best work. "IT is all about giving people the right tools," he said. "Our work is not exactly about the performance of the car, but we are increasing the capability of the engineers to operate. And this is happening continuously via better management of faults and better management of how they understand the performance of the cars."
This perspective challenges the common fear that AI will eliminate the need for expert judgment. In F1, where every millisecond counts, the ability to combine data-driven insights with deep experiential knowledge is exactly what separates top teams from the rest. The human does not simply supervise the machine; the human directs it, questions it, and ultimately decides which path to take.
Handcraft and High-Tech
The importance of human skill was visible during a recent visit to the Aston Martin F1 campus near the Silverstone racetrack. In one office, world-renowned aerodynamicist Adrian Newey was drawing new designs by hand, a practice that may seem out of place in a sport dominated by supercomputers and wind tunnels. Yet according to Pilotti, handcraft plays a crucial role in F1 performance. In a marginal gain business, small, tailored modifications by talented specialists can make all the difference.
Pilotti noted that new joiners to the team are often surprised by what they find inside an F1 organization. "They see what a team is like from the inside and they say, 'That's not what I thought it would be like. It involves more detailed handcraft,'" he said. This blend of traditional craftsmanship and cutting-edge digital tools is central to the team's philosophy. While AI can analyze enormous datasets and identify patterns that might escape the human eye, it is still the hand of the expert that shapes the final product.
The relationship between handcraft and technology is not a contradiction. Rather, it is a collaboration. An aerodynamicist may sketch a new rear wing concept on paper, but that sketch must be tested through simulations, validated in wind tunnels, and refined based on data collected from hundreds of sensors on the car. At every stage, human experience guides the process, deciding which avenues are worth pursuing and which are dead ends.
Agentic AI and the Future of F1 Software Development
Aston Martin F1's IT department is currently prioritizing projects that refine enterprise applications and develop trackside systems. AI agents are being applied tactically to the software development process, and the team is exploring how AI can improve optimization, including across ERP systems. These are not experimental projects meant to showcase technology for its own sake; they are practical efforts to improve the speed and quality of decision-making.
Pilotti explained that the end goal is to make data access seamless for users. "It's where the end user uses data without any interaction with IT. That's the end goal -- being seamless," he said. "Whatever resources they need for their rear wing design, for example, they're immediately available exactly in the format and the density they require, without having to wait three months for new systems. The future is about modular flexibility, so that the infrastructure can adapt to the team's data requirements."
This vision requires a shift in how IT teams work. Instead of building monolithic systems that take months or years to deploy, the team is moving toward modular, flexible infrastructure that can be reconfigured quickly. AI agents can help by automating routine tasks such as data preparation, code generation, and system monitoring, freeing engineers to focus on higher-level creative and strategic work.
The potential of agentic AI extends beyond the software development lifecycle. In the near future, agents could assist race engineers by sifting through telemetry data in real time, flagging anomalies, and suggesting adjustments to car setup. They could help strategists simulate countless race scenarios and weigh the risks and rewards of different pit stop strategies. But in all cases, the final decision remains with the human, who must account for factors that models cannot fully capture, such as driver confidence, weather changes, and the behavior of rival teams.
Partnering for Sovereign and Secure AI
No F1 team operates in isolation. Aston Martin F1 works with a network of technology partners to bring new capabilities to the track. One such partner is Cohere, an AI specialist that focuses on enterprise-grade models and sovereign deployment options. Ryan Lewis, head of UK and Northern Europe at Cohere, described how his company is working with the team to explore how AI models and agents can draw timely insights across telemetry, diagnostics, and simulation data.
"It's about empowerment," Lewis said. "We want to give people the power to automate the mundane things that are slowing them down from making executive decisions." By automating routine data processing and analysis, AI can help engineers and strategists spend more time on the creative and tactical aspects of racing.
A key concern for any F1 team is the security of proprietary data. Car designs, race strategies, and engineering data are among the most valuable assets a team possesses. Lewis emphasized that Cohere's approach addresses this concern by enabling deployment within the team's own infrastructure, keeping data and models together in a secure environment. "When you have data that's tucked away," he said, "and people would never even think about putting that information into a model or a system for fear of spillage of trade secrets, that challenge can be solved by building in such a way where you can deploy the technology within the infrastructure, keeping everything together and cohesive to produce results."
This sovereign AI approach allows F1 teams to benefit from the latest advances in machine learning without exposing sensitive information to potential leaks or external threats. It also allows models to be tailored to the specific language and context of motorsport, making their outputs more relevant and trustworthy for engineers who rely on them.
Experience as the Ultimate Differentiator
The growing role of AI in F1 raises an important question: if machines can analyze data faster and more accurately than humans, what is the enduring value of human expertise? Eric Ernst, commercial technology ambassador at Aston Martin F1, believes the answer lies in experience. "With AI, we can't outsource the experience," he said. "The experience is still with the team, but AI gives our people the cognitive scalability to do more than they can today."
Ernst pointed out that competitive advantages in auto racing come from a tightly knit ecosystem of trusted partners working together to solve the issues that F1 engineers identify. "It's about unleashing intelligence and using every partner not to adapt to the future, but to actually architect it -- taking complex challenges and providing clarity and momentum at each layer and each line of code at a time," he said.
F1 organizations have long used machine learning to analyze car data and identify performance signals. The latest generation of generative and agentic AI provides new opportunities to work proactively and develop timely, strategic responses to challenging scenarios. Yet even in the AI era, it is the engineer with years of knowledge who turns data into winning decisions. As Ernst put it, "The engineer is the person who's able to say, 'OK, I've got three options, and my experience tells me that's the option we should be choosing.' It's that experience that's crucial to driving value from AI."
Source: ZDNET News