Formula 1’s Grand Prix Week in Austin, Texas is turning into a software conference as much as a race weekend. On October 22, 2026, Axios Events will host a panel titled “Conversations on how Formula 1 is transforming business, technology, media and culture during Grand Prix Week in Austin, Texas,” scheduled for 6:50 p.m. CT, according to Axios Events. Austin Mayor Kirk Watson opens the session, which brings together Derek Chang, president and CEO of Liberty Media Corporation, and António Caçorino, founder and CEO of APEX, to talk through how the sport’s global growth is reshaping technology, media and culture.
The timing is not an accident. Behind the cars and the TV ratings, Formula 1 has quietly become one of the most aggressive adopters of cloud computing, machine learning and developer tooling in professional sports. Mercedes-AMG PETRONAS now runs its race strategy on Microsoft Azure. McLaren leans on Google Gemini to sort through hundreds of millions of simulated race scenarios. Red Bull Racing has deepened its relationship with Oracle, and Williams has folded Anthropic’s Claude into its operations. The Axios panel in Austin is set against that backdrop, and it gives the business side of F1, not just the engineering side, a stage to explain why a 200 mph car has become a proving ground for enterprise software.
Don't miss new tech stories on Google
Add Tech Insider once in the Google app and our stories appear in your news suggestions.
Inside the Axios Events Panel at Grand Prix Week
Axios Events has confirmed the panel’s lineup and format. Austin Mayor Kirk Watson will open the program, setting a local-civic frame for a conversation that Axios says centers on Formula 1’s global growth and its spillover effects on technology, media and culture. Derek Chang, who leads Liberty Media Corporation, the company that owns and commercially operates the Formula 1 group, is confirmed to speak. He will be joined by António Caçorino, founder and CEO of APEX, whose presence signals a focus on the operational and fan-engagement technology layer that surrounds the sport rather than purely the cars on track.
Axios has also built in a sponsored segment called “View from the Top,” featuring Pierre Gasly, driver for the BWT Alpine Formula One Team; Guy Martin, BWT Alpine’s global marketing director; and Marissa Dacay, global vice president of enterprise marketing at Adobe. Pairing a driver, a team marketing executive and a software company’s marketing chief in the same segment underlines how tightly F1’s commercial storytelling is now stitched to technology brands. Axios has not published additional details on venue capacity, livestream links or the exact runtime of each segment, and no pricing, attendance or financial figures tied to the event have been disclosed.
Why Formula 1 Has Become a Software Story, Not Just a Racing One
Ten years ago, an F1 technology story meant carbon-fiber layups or hybrid power units. In 2026, it increasingly means Kubernetes clusters, large language models and CI/CD pipelines. Every team on the grid collects telemetry from hundreds of sensors every session, and the sport’s governing commercial entity has pushed teams toward cloud-native infrastructure to process it fast enough to matter during a 90-minute race. That shift has turned F1 paddocks into showcases for cloud and AI vendors competing for the same enterprise customers that also buy AWS, Azure and Google Cloud GPU capacity for everyday business workloads.
The pattern mirrors what’s happening in software development more broadly, where AI coding assistants and agentic tools have moved from novelty to daily workflow in a similar span of time. Just as development teams now lean on tools like GitHub Copilot and competing AI coding assistants to cut iteration time, F1 engineering groups are using generative AI to cut the time between a sensor reading and a strategic call on pit stops or tire compounds. The parallel is not cosmetic. Several of the same vendors, including Microsoft and Google, are selling into both markets simultaneously.
Mercedes-AMG PETRONAS Hands Its Race Strategy to Microsoft Azure
Mercedes-AMG PETRONAS Formula One Team and Microsoft announced a multiyear technology partnership on January 22, 2026, according to the team’s official announcement and a report from StockTitan. The deal covers Azure cloud computing, enterprise AI, Microsoft 365, GitHub and simulation tools, and it is designed to connect the team’s factory operations in Brackley with trackside systems during race weekends.
StockTitan’s report on the announcement carried a detail that captures the scale of the problem Mercedes is trying to solve: the team’s cars generate more than 1.1 million data points per second, pulled from over 400 sensors per car. Microsoft’s Signal magazine, in an account of the partnership, described how the team uses Azure Batch to scale simulation workloads up and down during a Grand Prix weekend, letting strategists run far more scenario models in the window between qualifying and the race than a fixed, on-premises server rack could support.
The team is also piloting what Microsoft calls “intelligent virtual sensors,” a system that uses real-time sensor data combined with Azure’s AI tools to infer or fill in additional data streams without installing new physical hardware on the car. GitHub, meanwhile, has become part of the day-to-day engineering workflow, supporting collaboration on the design, modeling and simulation code that underpins the team’s performance work. For an operation under Formula 1’s cost-cap financial regulations, cloud elasticity through Azure Kubernetes Service matters because it lets the team burst compute capacity during simulation-heavy periods and scale it back down afterward, rather than paying for idle hardware year-round.
McLaren’s Hundreds of Millions of Simulations Run on Google Gemini
McLaren has taken a different vendor path. According to a report from TheNextWeb, the team runs close to 300 million race simulations before a single Grand Prix, and Google says its generative AI models can surface pit-window and tire-compound options at a scale that would be impractical to evaluate by hand. Google’s Gemini has been integrated into McLaren’s analytical platform specifically to help parse that volume of racing data and prioritize the strategic options that rise to the top.
The approach echoes how Google has positioned Gemini and its custom silicon elsewhere in its enterprise push. The company’s TorchTPU effort to compete with Nvidia’s GPU ecosystem is part of the same broader strategy: give large compute customers, whether they are racing teams or cloud tenants, a reason to standardize on Google’s stack for AI inference rather than defaulting to Nvidia hardware. McLaren’s willingness to put Gemini in the strategy loop is a visible, high-stakes endorsement that Google can point to in sales conversations well outside motorsport.
Red Bull Racing Doubles Down on Oracle
Red Bull Racing has expanded its existing relationship with Oracle, according to the same TheNextWeb report, deepening the use of Oracle’s systems inside the team’s operational and analytical environment. The report does not detail specific product names or dollar figures attached to the expanded deal, and no independent financial disclosure has confirmed contract value.
What is notable is the competitive framing. Oracle, Microsoft and Google are now running parallel plays inside the same sport, each attaching its brand to a different top team. That is a familiar pattern in enterprise technology, where vendors chase marquee logos to validate their platforms, similar to how chipmakers compete for headline AI customers to prove out new silicon. Oracle’s push into Red Bull’s data environment sits alongside its broader data-center and AI infrastructure ambitions, an area where pricing pressure has been intense across AI compute costs industry-wide this year.
Williams Rebuilds Its Engineering Pipeline Around Claude and CI/CD
Williams has taken arguably the most software-forward approach of any team on the grid. A technical document published by Brillio describes how the team modernized its digital engineering stack with automated data pipelines that ingest information every 15 minutes from enterprise resource planning, product-lifecycle-management and production-scheduling systems. Brillio also says the work included building unified CI/CD pipelines, giving Williams a secure, cloud-native foundation intended to speed up software delivery across its engineering organization.
Separately, TheNextWeb reports that Williams has incorporated Anthropic’s Claude into parts of its operational and race-strategy workflow, placing a large language model assistant inside the team’s engineering and decision-support stack. The combination, a near-real-time operational data foundation paired with an LLM assistant, is the kind of architecture more commonly associated with a Series B software startup than a 48-year-old racing team. It also illustrates how commoditized modern AI tooling has become: a mid-grid F1 team with a fraction of Mercedes’ or Red Bull’s budget can still stand up a comparable AI-assisted workflow using commercially available models and managed CI/CD tooling.
Formula 1’s Own AI Stack Runs on AWS
It is not just individual teams. Formula 1 as a series is reportedly running its own generative AI workflows on Amazon Web Services for race-day operations and media response, according to TheNextWeb. The reported use cases include triaging telemetry anomalies in near real time and surfacing broadcast-relevant context, with the goal of shrinking the gap between an on-track incident and an explanation that reaches viewers and commentators.
That use case sits closer to the kind of agentic coding and operations tooling that has spread through software teams generally, where AI agents increasingly handle first-pass triage before a human reviews the output. Developer teams watching tools like AI coding agents now merging a majority of pull requests on some teams will recognize the shape of the bet F1 is making: let a model do the first pass on a flood of data, and let humans make the final call under time pressure.
Comparing the Grid’s Cloud and AI Stacks
The table below lays out which cloud and AI vendors are tied to which teams, based on the reports cited above. Dollar values and contract lengths beyond the Mercedes-Microsoft deal have not been independently disclosed, so this comparison focuses on reported platforms and use cases rather than deal size.
| Team / Entity | Primary Tech Partner | Core Tools | Reported Use Case |
|---|---|---|---|
| Mercedes-AMG PETRONAS | Microsoft | Azure Batch, Azure Kubernetes Service, GitHub, Microsoft 365 | Race strategy simulation, factory-to-track compute, virtual sensors |
| McLaren | Gemini | Up to ~300 million pre-race simulations for pit and tire strategy | |
| Red Bull Racing | Oracle | Oracle cloud/data systems | Operational and analytical environment |
| Williams | Anthropic / Brillio / Atlassian | Claude, CI/CD pipelines, 15-minute data ingestion | Race-strategy decision support, near-real-time operations data |
| Formula 1 (series) | Amazon Web Services | Generative AI workflows | Telemetry anomaly triage, broadcast context generation |
| Aston Martin | CoreWeave | GPU cloud infrastructure | Reported compute partnership |
The Business Logic: Why Tech Giants Want Pit Lane Billboards
Liberty Media Corporation, under Derek Chang’s leadership, has spent the past several years turning Formula 1 into a global media and entertainment property rather than a niche motorsport. That commercial expansion is precisely the backdrop for the Axios Events panel in Austin, which frames the conversation around F1’s growth and its reach into technology, media and culture broadly, not just lap times.
For cloud and AI vendors, a logo on a car or a case study with a famous team functions as a marketing accelerant that is hard to replicate through traditional enterprise sales. A viewer who has never heard of Azure Batch or Kubernetes autoscaling can still watch a Mercedes strategist make a split-second pit call and associate that competence with Microsoft’s brand. The same logic applies to Google’s Gemini push with McLaren and Anthropic’s quieter placement of Claude inside Williams’ stack. Technology companies are using Formula One as a launchpad and spotlight for their own AI products or rebrandings, one industry analysis noted of the trend, a dynamic that lines up with how aggressively AI vendors have pursued visible, performance-driven partnerships across sports and entertainment over the past year.
From Pit Wall Radios to GPU Clusters: A Short History of F1 Tech
Formula 1’s relationship with computing has always moved in step with the broader tech industry, just with a bigger budget and a tighter deadline. Teams used basic radio telemetry in the 1990s mainly to confirm a car had not broken down. By the 2000s, teams had built dedicated trackside data centers, shipping server racks to every Grand Prix so engineers could crunch lap data between sessions. The 2010s brought the first wave of cloud partnerships, with teams experimenting with early machine learning models for tire degradation and aerodynamics simulation.
What’s different in 2026 is the depth of integration. Mercedes is not simply storing data in Azure, it is running its core strategy simulations there during the race itself. Williams is not just using a chatbot for internal documentation, it has wired an LLM into live decision support. The jump from “cloud as storage” to “cloud and AI as a real-time decision engine” mirrors the same transition that has played out in software engineering generally over the past three years, as AI moved from autocomplete suggestions to autonomous agents handling entire workflows.
What People Inside the Technology and Racing World Are Saying
A Mercedes-AMG PETRONAS F1 Team strategist, quoted in an interview with Microsoft’s Signal magazine, described the practical effect of moving simulations to the cloud this way: “Azure Batch has revolutionized our race strategy – scaling thousands of simulations in real time, we can ramp up massive compute during the race so we get… insight when it matters most.”
A Red Bull Racing representative, discussing the team’s Oracle-powered AI tools in comments reported by Reuters, framed the technology as a force multiplier for the engineering staff rather than a replacement for them: “So it’s really playing into the strength of AI as an enabler for our team. Allowing them (engineers) to focus on the core responsibilities they have and perform better at what they do.”
A technology industry commentator, assessing the wave of vendor deals across the grid in the same Reuters report, put the commercial motive bluntly: “These blue-chip companies are using Formula One as a launchpad and spotlight for their own AI products or re-brandings.” That read lines up with how Microsoft, Google, Oracle and Anthropic have each attached themselves to a different top team rather than competing for the same single sponsorship slot.
F1 Technology Partnerships Timeline
| Date | Team / Entity | Partner | Deal Type |
|---|---|---|---|
| Jan. 22, 2026 | Mercedes-AMG PETRONAS | Microsoft | Multiyear Azure and enterprise AI partnership |
| 2026 (reported) | McLaren | Gemini integrated into race-strategy analytics platform | |
| 2026 (reported) | Red Bull Racing | Oracle | Expanded operational and analytical technology partnership |
| 2026 (reported) | Williams | Anthropic | Claude placed inside race-strategy and operations workflow |
| 2026 (reported) | Williams | Brillio / Atlassian | CI/CD and near-real-time data pipeline modernization |
| 2026 (reported) | Aston Martin | CoreWeave | GPU cloud infrastructure partnership |
| Oct. 22, 2026 | Liberty Media / Axios Events | Panel discussion | Austin Grand Prix Week conversation on F1’s business, tech, media and culture reach |
Five Predictions for F1’s Software Stack Beyond 2026
- More teams will pair proprietary telemetry models with commercial large language models, following the Williams and McLaren template, rather than building every layer of the stack in-house.
- Cloud vendors will push beyond sponsorship into deeper technical integration contracts, using the Mercedes-Microsoft deal as the template other vendors pitch to remaining unsigned teams.
- Expect more generative AI tools aimed at broadcast and fan-facing content, extending the pattern already reported in Formula 1’s AWS-based race-day media workflows.
- Mid-grid teams with smaller budgets, like Williams, will increasingly use AI-ready digital backbones as a way to close the performance gap with better-funded rivals, echoing how smaller software teams use AI coding agents to compete with larger engineering organizations.
- Expect more crossover business-and-technology events timed to Grand Prix weekends, following Axios Events’ Austin panel, as F1’s commercial growth keeps attracting conversations that go beyond the racing itself.
Market Impact: A Software Showcase With Real Stakes
For Microsoft, Google, Oracle and Anthropic, the stakes in these partnerships go beyond the paddock. Each company is fighting for enterprise AI market share in a year when AI infrastructure spending has dominated earnings calls across the technology sector. A visible, high-performance use case like F1 race strategy gives each vendor a story to tell enterprise customers who are evaluating the same tools for far less glamorous workloads, like supply-chain forecasting or fraud detection. It also gives Formula 1 teams, which operate under a hard cost cap, a way to access enterprise-grade compute and AI tooling that would otherwise be difficult to justify building in-house.
The risk, which neither the teams nor the vendors have publicly addressed in detail, is dependency. A team that wires a single vendor’s cloud and AI tools deeply into live race-day decisions is also betting that vendor’s infrastructure does not go down during a Grand Prix. No outage or reliability incident tied to any of these F1 partnerships has been reported as of this writing, but the architecture now carries real operational weight that a simple sponsorship deal never did.
Frequently Asked Questions
What is the Axios Events panel at Austin’s Grand Prix Week about?
Axios Events is hosting a panel on October 22, 2026, titled “Conversations on how Formula 1 is transforming business, technology, media and culture during Grand Prix Week in Austin, Texas,” scheduled for 6:50 p.m. CT, focused on F1’s global growth and its influence on technology, media and culture.
Who is speaking at the Axios F1 technology panel?
Confirmed participants include Derek Chang, president and CEO of Liberty Media Corporation, and António Caçorino, founder and CEO of APEX. Austin Mayor Kirk Watson opens the event. A sponsored segment, “View from the Top,” features Pierre Gasly, Guy Martin and Marissa Dacay of Adobe.
Which cloud provider powers Mercedes-AMG PETRONAS’s race strategy?
Mercedes-AMG PETRONAS runs its race-strategy simulations and factory-to-track computing on Microsoft Azure, under a multiyear partnership announced in January 2026, using tools including Azure Batch, Azure Kubernetes Service and GitHub.
Does McLaren really use Google Gemini for race strategy?
According to reporting from TheNextWeb, McLaren has integrated Google’s Gemini into its analytical platform to help process close to 300 million pre-race simulations and prioritize pit-window and tire-compound options.
Which F1 team uses Anthropic’s Claude?
Williams has incorporated Anthropic’s Claude into parts of its operational and race-strategy workflow, according to TheNextWeb, alongside a modernized CI/CD and data-pipeline architecture built with Brillio and Atlassian tools.
How much data do Formula 1 cars generate during a race?
Mercedes-AMG PETRONAS cars generate more than 1.1 million data points per second from over 400 onboard sensors, according to figures tied to the team’s 2026 Microsoft partnership announcement.
Why are cloud and AI companies sponsoring individual F1 teams instead of the whole sport?
Each major vendor, including Microsoft, Google, Oracle and Anthropic, has attached itself to a different top team, giving each one a distinct, highly visible performance story to point to in enterprise sales conversations rather than competing head-to-head for one sponsorship slot.
Is Formula 1 itself, not just individual teams, using AI tools?
Yes. According to TheNextWeb, Formula 1 as a series reportedly runs generative AI workflows on Amazon Web Services to triage telemetry anomalies and generate broadcast-relevant context during race weekends.
