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The BMW Group has shifted its engineering ambitions into a higher gear by joining forces with Mistral AI to push artificial intelligence deeper into the world of crash simulation. The partnership is aimed at lifting the quality, accuracy, and speed of complex engineering tasks, and it marks the opening move in a broader plan to scale domain-specific AI across further parts of vehicle development and the wider BMW Group value chain.
According to Dr. Franz Decker, CIO and Senior Vice President of the BMW Group, industrial data sits at the heart of turning artificial intelligence into real value creation. By combining the carmaker’s engineering datasets with Mistral AI’s model training capabilities, the two companies aim to build specialised AI tools that genuinely support the kind of complex development work behind every new BMW rolling off the line.
The scale of the challenge is staggering. Each week, the BMW Group runs thousands of virtual crash simulations, generating a vast pool of engineering data on vehicle structures and material behaviour. Over time, that effort has built a historical archive of more than one petabyte of crash simulation data, providing highly detailed insights and forming a unique foundation on which to train an industrial AI model purpose-built for automotive safety.
To scale this approach, the BMW Group is focusing on what it calls Large Industry Models, or LIMs. These are AI systems trained on industry-specific engineering and simulation data drawn from vehicle development and safety testing. Unlike general-purpose AI tools, LIMs embed domain-specific knowledge straight into the model itself, which calls for not only industrial data but also deep expertise and technical environments that allow the AI to learn directly from BMW’s own development processes.
Mistral AI’s Chief Revenue Officer, Marjorie Janiewicz, framed industrial AI as the next frontier for the technology, noting that industry-specific models can tackle complex engineering challenges such as crash simulation. For the BMW Group, the partnership underlines just how important industrial data has become for the next phase of data-driven value creation and strengthens the wider AI and innovation ecosystem the company is building around its vehicles.
