This is how BMW is preparing to integrate AI into all its operational processes.

The German automotive group BMW Group has already deployed hundreds of artificial intelligence (AI) applications throughout its entire value chain and believes that in the near future, almost every operational process will be supported by AI .

 

Amidst ongoing debate about whether the 'AI bubble' will burst anytime soon, BMW is clearly one of the companies making a strong bet on the long-term future of this technology. The German automaker, renowned for its consistent vehicle quality over the years, is integrating AI into numerous different areas and continuously expanding its deployment.

According to Marco Gorgmaier, Vice President of Enterprise Platforms, Data and AI at BMW Group, the company is expanding the application of AI across its entire value chain, from development and production to sales. He stated that in the near future, every process within the BMW Group will be supported by AI. In fact, the company already has hundreds of AI use cases in mass production.

 

He also emphasized that the main drivers of this transformation are very clear business factors: improving operational efficiency, fostering innovation, and ensuring a return on investment (ROI).

Meanwhile, Nicolai Martin, a member of the board of directors responsible for procurement and supplier networks at BMW, argues that digitalization and AI are no longer a story of the future. According to him, at BMW's procurement department, these two technologies have become an integral part of daily operations.

BMW also argues that to lead the digital transformation of the automotive industry, businesses need to build strong collaborative relationships. This is especially important within the supplier network, where all parties need to work transparently and towards common goals.

One of BMW's flagship initiatives is its participation in building Catena-X , described as the first open and collaborative data ecosystem for the automotive industry. This platform utilizes various AI technologies to help businesses across the value chain increase their resilience to risks, meet sustainability goals, and comply with legal regulations.

 

A key feature of Catena-X is its ability to calculate the carbon footprint of a product, from the raw material extraction stage to the final product completion. BMW previously tested this system with the grille of the BMW iX electric SUV produced in Landshut, thereby building a complete CO₂ data chain with partners in the supply chain.

Alongside its data platforms, BMW is also building an internal AI infrastructure for the entire enterprise. The company has developed a self-service AI generative platform that allows employees easy access to AI tools and the ability to build their own applications for work. This system facilitates the development and deployment of AI solutions across all departments within the company.

Specifically, the BMW Group AI Assistant allows even employees without a technical background to create their own AI solutions and integrate them into workflows. This enhances efficiency and productivity, while an integrated AI governance framework ensures the safe and compliant use of this technology.

BMW also adopts an open technology strategy to avoid dependence on a single provider of a specific language model. This allows the company the flexibility to choose and combine various AI technologies.

 

In product development, AI is used for engineering tasks requiring large volumes of simulation, such as crash testing, aerodynamic studies, or scenarios related to autonomous vehicles. Thanks to AI simulations, BMW can reduce its reliance on physical prototypes and shorten vehicle development cycles.

At the Landshut plant, BMW also operates an AI lab where employees can directly test new AI technologies and explore their potential. According to Nicolai Martin, AI is now being used in component manufacturing to optimize production processes and ensure high-precision quality control.

Beyond development and manufacturing, BMW is also integrating AI into its procurement operations. The Tender Assistant tool supports the procurement team in creating tender documents by selecting suitable templates and automatically generating content based on the latest template data, best practices, and methods from previous projects.

Meanwhile, Offer Analyst helps analyze and compare bids through an interactive interface, allowing users to review legal factors and key criteria to assess whether a supplier meets the department's requirements.

 

These two tools are integrated into the AIconic system, a multi-agent AI platform that provides a central chat interface. Thanks to natural language processing technology and intelligent search algorithms, the system helps employees easily research suppliers, market trends, and internal data to make data-driven purchasing decisions.

AI also plays a crucial role in the transformation of BMW's factories into connected digital production facilities following the BMW iFACTORY model. According to Marco Gorgmaier, the company now operates hundreds of AI applications in mass production.

One example is the AIQX platform used for monitoring production line quality. The system analyzes sensor and image data in real time, allowing for immediate detection and correction of errors, thereby improving product quality and reducing defect rates.

In addition, BMW is also researching humanoid robots capable of automatically performing complex assembly tasks, and developing intelligent transport systems to optimize logistics operations within the factory.

According to BMW leaders, expanding AI across the organization is not about chasing a fleeting technological trend, but rather a long-term strategy aimed at unlocking new levels of efficiency and supporting faster, smarter decision-making.

BMW also believes it has a responsibility to lead the automotive industry into a new digital era. However, this journey can only succeed if the entire supplier network participates, collaborates transparently, and shares a common vision.