How AI Will Soon be Used to Support Every Process at BMW

The jury may be out on whether the AI bubble will burst, but BMW is one business that is betting on its long-term future.

The German automotive manufacturer, long known for the consistent high quality of its vehicles, is incorporating AI into hundreds of areas – and predicting that soon every process will be AI-supported.

BMW is scaling AI capabilities across development, production and sales operations. It has also established a Group-wide AI platform that enables custom solutions ranging from process optimisation in manufacturing to generative AI in customer communications.

Marco Gorgmaier, VP Enterprise Platforms and Services, Data, AI, BMW Group, says: “We’re scaling artificial intelligence along the value chain, from development and production through to sales.

“In the foreseeable future, every process at the BMW Group will be AI-supported. We already have hundreds of use cases in series production today.”

He says the transformation is driven by business imperatives. "The key drivers behind it all are efficiency, innovation and a clear focus on ROI," he explains.

Dr Nicolai Martin, Member of the Board of Management of BMW AG, Purchasing and Supplier Network, says digitalisation and AI have become operational realities rather than future aspirations.

"At the BMW Group Purchasing Division, digitalisation and artificial intelligence are no longer just future topics – they are part of our daily reality," he says.

The company believes leading the automotive industry's digital transformation requires collaborative partnerships.

Nicolai says this approach extends throughout the supplier network, working transparently with shared objectives.

Digital collaboration platforms

BMW Group is a driving force behind Catena-X, described as the first open and collaborative data ecosystem for the automotive industry.

The platform, which leans heavily into AI for its core operations, enables partners within value chains to address resilience, sustainability goals and regulatory compliance through digital collaboration.

The system allows calculation of product carbon footprints, from raw material extraction to final products.

Nicolai cites a demonstration project involving the BMW iX kidney grille produced in Landshut, where BMW Group and its partners modelled a complete CO2 data chain.

"Thanks to Catena-X, it is possible to calculate the product carbon footprint across the entire value chain – from raw material extraction to the final product," he says.

The integration of AI with such platforms enables process optimisation, early risk identification and more efficient resource utilisation.

These capabilities are being deployed in component production facilities, where AI enhances manufacturing processes and quality inspections.

Enterprise AI infrastructure

Among many applications, BMW Group has developed a gen AI self-service platform that provides employees with straightforward access to AI tools.

The infrastructure supports development and scaling of AI applications across all company areas.

The BMW Group AI Assistant enables non-technical users to develop their own AI solutions and integrate them into work processes. This accessibility increases efficiency and productivity while an integrated governance framework ensures secure, compliant AI usage.

The company maintains a strategy of openness to different technologies to avoid dependence on specific language model providers.

Its investment in AI extends to engineering processes, including analysis of specifications documentation and technical standards. The objective is enhancing efficiency and precision in development work.

Product development applications

In product development, BMW applies AI to technical tasks involving extensive simulations.

These include crash testing, aerodynamics and autonomous driving scenarios, reducing dependence on physical prototypes and accelerating development cycles.

The company also operates an AI Lab at its Landshut facility.

Nicolai says: “Here in Landshut, we are already using the power of AI in component production – optimising manufacturing processes and quality inspections with precision and intelligence.

“And in our AI Lab, employees have the opportunity to explore cutting-edge AI technologies hands-on, discover their potential, and bring new ideas to life.”

AI tools support vehicle development through simulations that previously required physical testing. This shift enables faster iteration and more comprehensive testing scenarios than traditional methods allowed.

Procurement intelligence

BMW Group has also deployed AI-driven tools specifically for procurement operations.

The Tender Assistant – supports procurement teams in creating high-quality tender documents by selecting appropriate templates and generating content. The system incorporates trained sample cases, latest templates and proven best practices from previous tenders.

The Offer Analyst – streamlines analysis and comparison of tender documents through interactive engagement. Users can review legal aspects and key criteria to determine whether suppliers meet departmental requirements, providing foundations for informed purchasing decisions.

AIconic – The Tender Assistant and the Offer Analyst procurement tools integrate into AIconic, a multi-agent system offering a centralised chat interface. Natural language processing and intelligent search algorithms enable efficient research of suppliers, market trends and internal knowledge for data-driven decision-making.

Production transformation

AI implementation supports ongoing transformation of BMW plants into networked digital facilities under the BMW iFACTORY concept. Marco says the company already operates hundreds of use cases in series production.

AIQX is the AI quality platform for constant production line monitoring. Real-time analyses of sensor and image data allow immediate fault detection and elimination, enhancing product quality and reducing defects.

The manufacturer is also researching humanoid robots for autonomously performing complex assembly tasks.

Smart transport systems are being developed to optimise logistics operations further within production facilities.

AI in the driving seat

BMW’s belief in and commitment to artificial intelligence in its operations is clear – and it includes a determination to be a leader in the field.

Nicolai says: “We are now entering the next chapter: scaling AI across our organisation to unlock new levels of efficiency and to empower smarter, faster and more forward-looking decision-making.

“We believe it is our responsibility to lead the transformation of the automotive industry into a new digital era.

“And we know this journey can only succeed if we take our partners in the supplier network with us – collaboratively, transparently and with a shared vision.”

The scaling of AI across BMW is not inspired by the desire to follow a fad: it is purposeful, with leaders seeing it as a way to unlock new efficiency levels and enable smarter, faster, more forward-looking decision-making.