Can data find the first female Formula 1 driver?

Can data find the first female Formula 1 driver?

What does it take to become a Formula 1 driver?

Raw talent? Mental sharpness? Physical endurance?

For decades, the answer has been largely subjective – and the unspoken truth has been this: you need to be a man.

But what if we could rewrite that story? One where data – not tradition – identifies the next great racing talent. One where gender no longer dictates opportunity.

That’s exactly what OpenTech member Avenga (formerly Qinshift) is doing in a groundbreaking collaboration with the non-profit initiative More than Equal, co-founded by F1 legend David Coulthard and philanthropist Karel Komarek. Their shared mission is bold: to find and develop the first female Formula 1 world champion.

And the key to doing it? Data.

Not a question of strength. A question of system.

There is no physical reason – at any level of competition – why women can’t compete with men in motorsport. Still, in over 50 years, not a single woman has raced in Formula 1.

That’s not because women lack ability. It’s because they’ve been systematically overlooked.

It starts with go-kart, the entry-level discipline where racing dreams begin. From there, the path is clear: Formula 4, Formula 3, Formula 2, and finally Formula 1. But already at the first step, the system filters talent unfairly. Very few girls enter the sport to begin with – in large part due to the lack of female role models – and among those who do, sponsorship and support almost exclusively go to boys, shaped by decades of tradition and assumptions about who’s “worth investing in.”

More than Equal wants to change that. And together with Avenga, they’re doing it in a completely new way: by building a data-driven model to objectively identify and support talent, regardless of gender.

A global, passion-driven collaboration

From the outset, the ambition was to explore how AI could be used to support equality in motorsport. That idea quickly evolved – not into a generic tech experiment, but into the development of an advanced, long-term data model. A model designed not only to identify talent, but to follow and support each driver’s development over time. What emerged was a powerful collaboration between a non-profit, a global tech company, academic researchers, and motorsport experts – all working together to reshape how talent is seen and supported.

A growing movement

The strength of this project lies in the people behind it. From Avenga’s developers in Ukraine, to psychologists, race experts, everyone involved brings passion and purpose. The collaboration works because it’s built on shared belief – not just in data, but in what it can unlock when used right.

“With the right data, we can break old patterns and open doors that have been closed for too long. This project is about proving that talent knows no gender – and building the system to make that visible.” says Liselott Lading, Visionary transformation leader & digital strategist, Avenga.

For Avenga, it’s become part of company culture. Their name is on McLaren’s F1 cars. Their employees follow the project closely, engage in it deeply – even place friendly bets on the future of the drivers.

And for OpenTech, this is exactly the kind of initiative we champion: one where technology, research, and business come together to solve real, structural problems. Because sometimes, the fastest way forward… is to let the data drive.

Photo courtesy of: More than Equal, Avenga, Liselott Lading

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