In a sport defined by fractions of a second on the track, the fastest and most reliable decisions are increasingly made off the track by experienced professionals. That paradox is central to how Formula One teams are embracing artificial intelligence in the current era. While business leaders across industries worry about generative and agentic AI displacing workers, one of the most technology-intensive sports in the world is demonstrating that the human in the loop is more valuable than ever.
Aston Martin Aramco F1 offers a compelling case study. The team, headquartered near the Silverstone circuit in the UK, has made clear that its competitive edge depends not on replacing people with software but on pairing cutting-edge data systems with the judgment of engineers, aerodynamicists, and IT specialists who have spent years mastering their craft.
Small gains, huge impact
Formula One is a sport of marginal gains. A few milliseconds in a pit stop, a slightly more efficient rear wing, or a better tire strategy can be the difference between a podium finish and missing out on points. In this environment, data-driven insights can provide a critical edge, but those insights require interpretation by people who understand the car, the track, and the nuanced physics of racing.
Fabrizio Pilotti, CIO at Aston Martin Aramco F1, told reporters during a recent visit to the team's technology campus that the speed of iteration is what separates successful teams from the rest. "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."
That philosophy applies as much to IT systems as it does to the car on the track. Pilotti described his department as a performance-enhancing function, not a back-office support unit. The goal is to give engineers and designers the right tools to do their jobs more effectively. Whether that means better fault management, faster simulation feedback, or more accurate performance modeling, IT exists to amplify human capability rather than replace it.
Handcraft in a digital world
One of the most striking moments during the tour of the Aston Martin Aramco F1 headquarters was seeing renowned aerodynamicist Adrian Newey drawing new designs by hand in his office. Newey, widely considered one of the greatest car designers in F1 history, represents the value of deep expertise and tactile creativity in an industry increasingly dominated by simulation and machine learning.
Pilotti said that new joiners to F1 are often surprised by how much detailed handcraft remains part of the workflow. "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 does not mean the team rejects digital tools. On the contrary, simulation software, telemetry analysis, and AI-based optimizations are used throughout the design and race operations. But the most effective use of those tools comes when experienced humans direct the process. A computer can generate a thousand possible rear wing configurations, but only an expert can say which one is most likely to perform well in the context of a specific race, weather condition, and driver style.
Agentic AI and practical experimentation
The Aston Martin Aramco F1 IT team is currently exploring a range of AI applications, from enterprise resource planning systems to trackside software. One promising area is agentic AI, where software agents perform tasks autonomously with minimal human intervention. Pilotti says the team is applying AI agents tactically to software development and testing optimization, including across ERP systems.
"It's where the end user uses data without any interaction with IT. That's the end goal -- being seamless," Pilotti explained. "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 of seamless access to data is ambitious, especially in a sport where teams guard their intellectual property fiercely. Trade secrets, such as aerodynamic designs and race strategy algorithms, cannot be shared with public cloud models or external providers without risking leakage. That is why the team is working with partners such as Cohere to deploy sovereign AI models and agents within the team's own infrastructure, keeping sensitive data contained and secure.
Ryan Lewis, head of UK and Northern Europe at Cohere, explained at the Aston Martin Technology Forum that the collaboration is about "empowerment." He said: "We want to give people the power to automate the mundane things that are slowing them down from making executive decisions."
Lewis highlighted how Cohere aims to implement emerging technology securely in sensitive environments like F1. "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."
Experience cannot be outsourced
While technology partners provide critical infrastructure and expertise, the team's leadership is adamant that the core competitive advantage cannot be outsourced. Eric Ernst, commercial technology ambassador at Aston Martin F1, told forum attendees that AI enables cognitive scalability, but it does not replace the context and intuition that come from years of working in racing.
"With AI, we can't outsource the experience," Ernst said. "The experience is still with the team, but AI gives our people the cognitive scalability to do more than they can today."
This view is supported by the broader history of technology adoption in Formula One. For decades, teams have used machine learning to analyze car data, identify performance signals, and predict outcomes. But those models are only as good as the human engineers who decide which variables matter, how to weigh them, and what actions to take in response.
Ernst described the engineer as the person who can look at three options generated by an AI system and use experience to choose the right one. "It's that experience that's crucial to driving value from AI," he said.
A tight ecosystem of partners
The Aston Martin Aramco F1 team's approach to AI is built on a tightly integrated ecosystem of partners. No single vendor can provide all the capabilities needed for a modern F1 team, from aerodynamic simulation and telemetry analysis to ERP management and cybersecurity. Instead, the team works with a selection of specialized companies that can adapt their technologies to the fast-moving, high-stakes environment of racing.
Pilotti emphasized that the relationship with partners is iterative and collaborative. Rather than simply buying a product and expecting it to work, the team engages with partners to refine the technology through continuous feedback loops. This approach allows new systems to be tested, improved, and deployed in a matter of weeks rather than months.
"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," Ernst said.
This collaborative model may also offer lessons for other industries. Many organizations struggle to generate value from AI because they treat it as a simple technology replacement rather than an opportunity to augment human capabilities. The F1 team's experience suggests that the most successful AI implementations are those that start with the problems experienced professionals face and work backward to find the right tools.
Human in the loop remains essential
As generative AI and agentic services become more sophisticated, there is understandable concern about the future of work. But the example of Formula One shows that advanced technology can still benefit from human oversight. In fact, the more powerful the AI, the more important it is to have experienced professionals who can interpret its outputs and make high-stakes decisions.
The term "human in the loop" is often used as a safety mechanism, but in F1 it is a competitive strategy. The best results come from a blend of digital speed and human judgment. A skilled engineer can spot a flaw in a simulation that a model might miss. A veteran aerodynamicist can propose a creative design that no algorithm would generate. A race strategist can read the flow of a grand prix and adjust the plan in real time based on experience and intuition.
At Aston Martin Aramco F1, the vision of the future is not one where AI replaces the specialists in the technology campus or the engineers at the track. Instead, AI is transforming their jobs, automating routine tasks, and providing them with better information faster. The people remain the ones who make the final calls, and their skills are being sharpened rather than diminished by the new tools.
Pilotti summed up the philosophy simply: "IT is all about giving people the right tools. Our work is not exactly about the performance of the car, but we are increasing the capability of the engineers to operate." That focus on enhancing human capability, rather than replacing it, is what will define truly successful AI adoption in the years ahead.
Source: ZDNET News