
How AI is revolutionising F1 - Presented by Dell Technologies
We’ve collected data since the ‘80s, but AI has transformed how we use it

Read time: 10.4 minutes
AI has enjoyed a rapid rise to prominence in recent years, exploding across the wider world and developing even faster than people’s understanding of how to use it. Unlike many inventions from the last few decades, it came with no user manual but so many possibilities, especially in Formula 1, which shares one major trait in common with AI: it loves data.
Our team wasted no time exploring its potential benefits and has gradually introduced it into our everyday lives, to the point that we now no longer know how we’d live without it.
Our team loves data, but we’re only human and can only process so much, both due to time constraints and because too much data is simply overwhelming and counterintuitive. But not for AI, which can digest and cut through it, telling us precisely what is useful and what we can disregard. And the more data we feed AI, the smarter it gets.
Rather than keeping huge libraries worth of statistics that go largely unutilised, AI can tell us what we need and synthesize it into actionable insights. The time saving is astronomical. And not just time savings producing existing reports, but brand new types of learning are possible that we could have never attempted before AI. So much valuable data would have gone to waste.
As part of a new five-part series with Dell Technologies, our official innovation partner, we’ll explore how our use of data over the years has evolved and how AI has revolutionised it.

What is AI and why is it used in F1?
AI, short for Artificial Intelligence, learns by being fed data and instructions, detailing what the data is and how to use it. The more information it consumes and the more instructions it’s given, the better it gets at performing tasks.
At the McLaren F1 Team, we work closely with Dell Technologies who is an industry catalyst for AI innovation, to accelerate our use of this powerful technology. Utilising their AI Factory, a system of services, hardware, data management, and partner integrations, we can quickly operationalize all of the components required to plan and deploy our AI solutions.
The possibilities of AI are pretty much endless, especially in the longer term, but some current examples relevant to Formula 1 include organising and categorising data, spotting anomalies and mistakes, and even searching for images. It can also help us write instructions, emails, or any other form of copy.
Data dating back decades
We’ve been collecting data for a long time, dating back to Ayrton Senna and Alain Prost’s time at McLaren. Unlike most drivers at the time, Ayrton and Alain were both huge advocates of data collection because they could see the results translate on track.
But at the time, there was very little we could track, and it was all done physically with a stopwatch, a pen, and a pad of paper. We were mostly limited to how quickly a car was going around each section of the circuit.
By analysing that data, you could explore where other cars were quicker and use that to work out how - whether that was in braking and acceleration, the racing lines they were taking, or how they approached corners.

Ayrton Senna pictured analysing data in 1989
The evolution of data in F1
Our use of data has developed massively since the days of Senna and Prost. The first major revolution was when wireless transmission became available, allowing for data transfer from sensors on the car to a Dell Technologies data center.
The second significant change was in weight saving, with the car's sensors becoming considerably lighter and thus impacting speed less.
Data collection has snowballed since, and cars are now kitted out with 300-600 sensors during sessions, which transfer data to our Dell Technologies AI Factory. More are bolted on during practice when weight isn’t relevant and less during Qualifying and the Grand Prix when we need to be at our most nimble. The sensors measure everything from the engine and tyre temperatures to air intake, gear ratios and the airflow over our cars. The most significant differential, without doubt, is aerodynamic data.
Some of this data is used live during the session for operational reasons or to make decisions, and some is fed back to the team at the factory, who are working on future races and upgrades and use it to improve the car’s design and make it faster. Data can tell us what our car's strengths and weaknesses are - we can use that to enhance the strengths in the short term and to eliminate the shortcomings in the long term.

Covered in sensors, aero rakes measure the airflow across the car's bodywork
The flexibility of data
But it isn’t solely for performance-enhancing reasons. Much of the data we collect is operational and used to monitor and manage the car to ensure it’s running correctly.
“The cars are significantly more complicated now than ever,” Andrew explains. “They have electric hybrid engines, so we need to measure the battery voltages and charge, as well as the fuel, temperature, and oil pressure. Then there’s the gearbox, which is computer controlled to change gears faster than the blink of an eye, but can rip itself apart just as quickly if a problem isn't spotted immediately. As the car has become more complicated, we’ve adapted with it and collect data to manage it.”
Much of that data goes directly to the crew on the pit wall, who you’ll see scrolling through screens of data monitoring the car's health. All this work is done on Dell Technologies solutions specifically tailored for McLaren’s unique needs, and organised and optimised using AI.

The data gets sent to the McLaren pit wall
Championship-changing decisions
When Andrew first joined McLaren, he was one of a kind: the company’s first Data Scientist, but he now leads an entire team.
“Previously, we've collected data that we didn't know what to do with, but now, with AI and by working with Dell Technologies’ AI Factory, we can process the data in a much richer way to extract meaningful learnings from it.
“A lot of the hardware we use is very hard to get hold of. Every company in the world wants to get their hands on these, so we’re fortunate that we can leverage Dell Technologies and get access to this equipment before others are able to, which can give us a bit of an advantage.”
A lot of the hardware is actually bespoke to McLaren, created by Dell Technologies to match our exact requirements. And as well as providing us with the hardware, they work with us to ensure we’re getting the best out of it.
“If you’ve got a problem, they’ll work with you to ensure they’re providing the best kit to tackle that problem, using their list of industry-leading partners to provide a tailor-made solution,” Andrew adds.

Andrew was McLaren F1's first Data Scientist
When it comes to the data we use in session, whether that be a tweak to our setup in practice or a change in the Grand Prix, we need that data to be processed as quickly as it's generated to make decisions in real time. No human can work that quickly, with so much data to sift through, but AI can.
“If it's a decision related to pitting, you may only have a third of a lap before the car passes the pit lane, and after that, you’ve lost your opportunity, so you need to be fast. You could have terabytes and terabytes to analyse, which could take half a day or more to answer just one question without AI.
“But even when it comes to the team back at the factory working on the car’s development, speed matters. You may have five questions, and if it takes you half a day to answer each, that slows everything down. AI speeds all of that up, and the faster we can answer these questions, the faster we can develop the car and the more likely we are to win championships.”
As Official Technology Partner of the McLaren Group and McLaren Formula 1 Team, Dell Technologies brings its expertise as an innovation catalyst empowering McLaren to accelerate AI outcomes. Find out more here.