"How AI is Becoming the Ultimate Pit Crew in Formula 1"

July 01, 2026

Formula 1 has always been defined by speed — not just the velocity of the cars on track, but the speed at which teams process information, adapt strategy, and make split-second calls from the pit wall. In a sport where a tenth of a second often separates glory from also-ran, the teams that process data fastest have a genuine competitive edge. That's why an increasing number of F1 organizations are turning to artificial intelligence as their newest performance-enhancing tool, and McLaren's latest partnership with Google Gemini may be the highest-profile example yet.

A Livery with a Deeper Story

Ahead of this weekend's British Grand Prix at Silverstone, McLaren unveiled a special livery created in collaboration with Google. The design draws inspiration from the McLaren M2B, the team's very first Formula 1 car, serving as a visual bridge between the team's historic roots and its forward-looking technology push. While the livery naturally grabs the headlines — and the photos from Silverstone will no doubt be striking — the real story lies beneath the paint.

Dan Keyworth, McLaren's executive director of performance technology, described the partnership as "authentic" with a singular goal: "to make the car go faster." That's not marketing speak. The collaboration has already produced tangible tools that are changing how the team works on race weekends.

Natural Language Meets Race Data

The centerpiece of McLaren's AI push is a custom Gemini-powered live data interface. During qualifying sessions and race weekends, McLaren's engineering team can query vast streams of telemetry data using natural language. Instead of manually cross-referencing spreadsheets, cross-referencing multiple data streams, and dedicating significant human hours to a single comparison, an engineer can simply ask the system a question and get an answer in seconds.

"Now, they can compare with other drivers and competitors and give us insights on how we can improve ourselves," Keyworth noted. For a sport built on marginal gains, collapsing a "huge amount of human power" into a query-and-response cycle doesn't just save time — it fundamentally changes what kind of analysis becomes feasible mid-weekend.

The Broader F1 AI Wave

McLaren is far from alone in this push. Across the grid, every major team is exploring how AI can unlock performance:

Oracle Red Bull Racing is developing an AI-powered strategy agent capable of processing race conditions and suggesting optimal pit strategies in real time.
Mercedes-AMG Petronas is using Microsoft Azure to expand AI-supported simulation and race modeling, enabling engineers to test more setup configurations before a car ever hits the track.
Aston Martin Aramco has signed AI partnerships with Cohere and Arm, exploring everything from language models for technical documentation to edge computing on the car itself.

What's notable is that these aren't replacement technologies. No one is suggesting AI should take over race strategy entirely or replace the intuition of a seasoned race engineer. Instead, the tools are designed to augment human judgment — to surface relevant information faster so that the humans can make better, more informed decisions.

Driver Perspectives

Oscar Piastri, McLaren's young driver, offered a grounded perspective on the technology. He described a major part of his job as explaining what he needs from the car and helping engineers connect his felt experience to the data they see. AI helps bridge that gap.

"All the analysis we do, summarizing meetings and briefings, all that information I get through the team," Piastri said. "Now, with AI… it improves efficiency."

Efficiency is an understated value in F1. When every minute of a practice session is packed with data collection and setup changes, saving time on analysis means more time for iteration. It's the compounding effect — small gains in efficiency across dozens of sub-processes — that ultimately shaves tenths off a lap time.

Navigating the Rulebook

One of the more creative applications McLaren is exploring is a regulation bot powered by Gemini. Formula 1's technical regulations, published by the FIA, run hundreds of pages and are updated regularly. Teams must ensure their designs comply with every clause, and navigating this rulebook has historically required deep domain expertise and hours of manual searching.

Piastri described the challenge succinctly: "There's a lot of new rules and regulations and lots and lots of pages. I think AI is a great way of being able to find information quickly, especially when it comes to knowing some of the more unique rules and the ones you don't often run into every day."

This kind of application extends well beyond F1. Regulation compliance, legal discovery, and technical standards navigation are pain points across industries. McLaren's experiment with a regulation bot could serve as a proof-of-concept for AI-assisted compliance workflows far beyond motorsport.

What This Means Beyond the Race Track

The F1-to-general-industry pipeline is well established. Technologies that prove themselves in the crucible of race weekend conditions — high stakes, limited time, extreme data volumes — often find their way into broader commercial applications. Hybrid energy recovery systems, advanced telemetry, carbon-fiber manufacturing, and simulation software all originated or were perfected in F1 before spreading to other sectors.

AI-assisted data analysis is no different. The tools McLaren, Red Bull, Mercedes, and Aston Martin are building today could well preview how enterprises will interact with data in the coming years: natural-language interfaces over complex data pipelines, automated summarization of technical documents, and AI agents that augment rather than replace human expertise.

As Piastri put it: "I think that kind of capability can expand in the future to lots of different areas, finding solutions quickly. We'll have to see where the technology goes."

At Silverstone this weekend, fans will see a car wrapped in a livery that honors McLaren's history. But underneath the paint, the team is quietly building the future of racing — one AI query at a time.

Based on reporting from Fast Company