For decades, Formula 1 success has been measured in the workshop as much as on the racetrack — in the hundredths of a second shaved off a pit stop, the marginal gains found in a wind tunnel, the extra lap of data squeezed out of a Friday practice session. As the sport enters its most sweeping regulatory shake-up in a generation, one team has decided that the next great source of those marginal gains isn't hardware at all. It's software — specifically, artificial intelligence woven into nearly every layer of the organization.
Atlassian Williams F1 Team, one of the grid's last fully independent constructors, has spent the past eighteen months quietly assembling one of the most ambitious AI and data strategies in the sport. It spans race strategy, aerodynamic design, financial planning, garage logistics, and the day-to-day working culture of the team itself. Partnerships with Atlassian, Anthropic, Brillio, and Neural Concept — alongside a landmark leadership hire — tell the story of a team that has decided technology and teamwork are no longer separate disciplines, but the same discipline.
A New Kind of Signing
Williams made its intentions clear early in 2026 when it appointed James Smith as the team's first Chief Information Officer — a hire as significant, in its own way, as any driver announcement. Smith arrives with a decade of experience at DeepMind and Google, where he helped build Android's data platform, and with the added credibility of having founded his own AI company, Human Native.
In a statement announcing the appointment, Smith said he was joining "at a moment when data and AI are becoming increasingly important to performance both on and off the track," adding that his focus would be on helping the team "move quickly, use AI pragmatically, and turn complex ideas into practical advantage."
Team Principal James Vowles was equally direct about what the hire signals for the wider organization. "Success in Formula 1 has always been about combining technological innovation with the best people to deliver on track," he said, before framing the moment in even starker terms: with technology developing at breakneck pace, he argued, "the latest battleground in F1 is the ability to harness data and AI across all parts of the team." It is a battleground, Vowles suggested, that increasingly separates the teams that are merely competing from the teams built to win.
The appointment is emblematic of a broader transformation under Vowles' leadership — one in which the once-tongue-in-cheek image of a Formula 1 car being assembled by spreadsheet has been replaced by a genuinely modern, technology-first operating model.
Claude Joins the Pit Wall
That philosophy reached a new milestone in February 2026, when Williams and Anthropic announced a multi-year partnership naming Claude as the team's "Official Thinking Partner" — a title that reflects a deliberate choice of language. Rather than positioning AI as an autonomous decision-maker, Williams has framed Claude's role as augmenting the judgment of the engineers and strategists who already do the thinking.
Under the agreement, Claude is being integrated across the organization to support race strategy, car development, and day-to-day operations, with Anthropic pitching the model's strengths in reasoning through complex, high-pressure problems. The partnership carries visible weight, too: Claude branding appeared on the FW48 livery from its February 3rd reveal ahead of the season opener in Melbourne, making the collaboration one of the more prominent AI-branded partnerships on the current grid.
Vowles described the tie-up as a natural extension of the team's rebuild, noting that Formula 1's fast-moving technology and information landscape means teams "can often make big strides forward from week to week – never mind from season to season, or from one set of regulations to another." For a team that has been steadily climbing the constructors' order since 2023, that incremental, compounding progress is exactly the point.
Anthropic, for its part, framed the partnership as a meeting of like-minded underdogs. Mike Krieger, Co-Lead of Anthropic Labs, said Formula 1 is "ultimately about the pairing of human endeavour and technical excellence," and that Williams' ability to "punch above their weight for years" made it exactly the kind of team Claude was built for. Andrew Stirk, Anthropic's Head of Brand Marketing, echoed the sentiment, pointing to Williams' status as one of F1's last truly independent teams and its reputation for competing "on the quality of their thinking and their attention to detail" as the deciding factor in choosing the partnership.
Central to how Williams talks about the Claude partnership is a clear line between support and substitution. Vowles has been consistent on this point, explaining that AI has increasingly assisted engineers "in lots of different areas, but crucially not replacing their decision-making" — a combination he considers the right one, with Claude simply extending the capabilities available to the team's subject-matter experts. That same long-term thinking extends to how Williams frames its partnerships more broadly: not as sponsorship arrangements or logos on a car, but as genuine collaborations built around shared values and ambition.
Teamwork as a Technology Problem
If Anthropic's role is to sharpen thinking, Atlassian's partnership — in place since 2025 — has focused on something arguably just as decisive in a cost-cap era: how efficiently a few hundred people can work together under relentless time pressure.
Andrew Boyagi, Atlassian's Customer CTO, described the tie-up as a genuine partnership rather than a sponsorship, built on a shared belief that in Formula 1, "the success goes to the teams that have the best teamwork and the best technology." The results in year one were tangible: Williams climbed from ninth in the constructors' championship in 2024 to fifth in 2025, a jump worth millions of dollars in additional prize money.
Much of that shift has been driven by Atlassian's Rovo AI tools, which Boyagi says have fundamentally changed how the team allocates its time. Before the partnership, AI adoption within Williams was relatively low; afterward, Boyagi notes that 63% of the team reported having more time for strategic, high-value work, having delegated repetitive, low-value tasks to AI. Baseline data collected between October 2025 and March 2026 found that 92% of the team now feel they are working on the right organizational priorities, while trust in internal documentation rose by 200% over the same period — a marker, Boyagi says, of how central reliable knowledge-sharing is to productivity in a fast-moving environment like Formula 1.
Two examples stand out. The first is a new Fault Management tool that helps prevent mechanics — often working at pace, trackside or back at the factory — from logging the same issue multiple times, a redundancy that wastes precious time and resources in a sport where every dollar of the cost cap counts. The second is garage setup: with the team travelling to 24 races worldwide and transforming an empty garage into a fully functioning technical hub at each stop, Atlassian redesigned the process so that tasks automatically populate Jira boards by category and team member, replacing what had previously been a manual, pen-and-paper checklist system.
The cultural shift extends to the drivers as well. Boyagi recounted a moment when Alex Albon was debating a car setup decision with his engineers — a debate ultimately settled by asking Rovo, which sided with Albon rather than the engineering team. The anecdote, Boyagi suggests, illustrates the value of Atlassian's underlying Teamwork Graph, which connects data across the organization so that answers can draw on connections a human might take too long to piece together manually.
From the engineering side, Technical Director Matt Harman has praised the time savings the tools deliver, describing the goal as building systems that let the team be more collaborative while giving people "more insight, more ideas" so they can spend less time on business-as-usual tasks. The result, in Harman's words, is "less meetings, more insights" — engineers getting instant access to what they need without needing to convene a meeting to get it.
Building the Single Source of Truth
Behind the driver-facing headlines sits a less visible but equally critical challenge: making sure the team's underlying data is trustworthy and current enough to act on. Formula 1 teams operate across a dense web of operational, cost, and telemetry systems, and for Williams, much of that information — while accurate — was historically scattered across disconnected platforms. Operational data lived in ERP systems, component lifecycle information sat in separate PLM environments, and production scheduling and cost data occupied yet other layers, with little communication between them.
That fragmentation had real consequences. Cost engineers struggled to access up-to-date car delivery information, while planning and procurement teams often had to make calls based on data that was hours old, if not incomplete.
Williams addressed the problem by naming Brillio as its Official Data and AI Services Provider, tasking the company with building unified data pipelines that automatically ingest information from across the team's core systems every 15 minutes. The result is a single source of truth spanning engineering and operations — stronger financial oversight, richer performance analytics, and, perhaps most importantly for the future, a scalable data foundation designed specifically to support further AI and machine learning applications as the team's ambitions grow.
Designing the Car Itself
AI's influence at Williams isn't confined to logistics and strategy — it extends into the aerodynamic design of the car itself, an area long considered the most technically demanding in the sport. Since 2018, Swiss startup Neural Concept has been developing a machine-learning platform called Neural Concept Shape (NCS), and an evolution of that technology is now used by four of the ten teams on the current F1 grid, Williams among them.
NCS applies machine learning to computational fluid dynamics, a field traditionally reliant on highly trained engineers running time-intensive 3D simulations. Rather than replacing that expertise, NCS operates in what its creators call "co-pilot mode": an engineer uploads an existing 3D shape, and the system's neural network suggests possible aerodynamic refinements, which the engineer then evaluates, tests, and iterates on further.
The technology's origins are a reminder of how far machine-learning-assisted design has travelled in a short space of time. Founder and CEO Pierre Baqué, working out of the École Polytechnique Fédérale de Lausanne's Computer Vision Laboratory, first applied the approach to help a French university cycling team break the world record for bicycle speed — a project that, within two iterations, produced a shape closely resembling the existing record holder, and eventually contributed to what Baqué describes as the most aerodynamic bicycle in the world. From there, the same underlying technology found its way into aerospace and automotive applications with companies like Airbus, Safran, Bosch, and Mahle, before arriving in the paddock as a tool now shaping the cars that Williams and its rivals bring to the grid.
Thinking Differently, Together
Taken together, these initiatives sketch a team that treats artificial intelligence not as a single tool bolted onto existing processes, but as a connective layer running through the entire organization — from the shape of the car, to the data underpinning financial and engineering decisions, to the daily working rhythms of the people who build and race it.
What unites the Atlassian, Anthropic, Brillio, and Neural Concept partnerships is a consistent philosophy: AI at Williams is designed to extend human expertise rather than override it. Engineers still make the calls on car setup; strategists still own the decisions made on the pit wall; designers still choose which aerodynamic path to pursue. What has changed is the speed and confidence with which those decisions can be made, and the amount of low-value work that no longer stands between Williams' people and the problems that matter most.
For a team built on nine Constructors' Championships and a long tradition of independent thinking, that may be the most fitting innovation of all: using the most advanced technology available not to replace the judgment that built Williams' reputation, but to sharpen it.