The BMW Group is accelerating the digital transformation of its manufacturing operations by embedding artificial intelligence deeply into physical processes. A central focus of this strategy is Physical AI, a concept that unites digital intelligence with machinery and robotics. This integration allows systems like humanoid robots to function effectively within live production environments. For the first time, this approach is being introduced in Europe through a pilot project at the company’s Leipzig plant, where humanoid robots will be tested in the assembly of high-voltage batteries and component manufacturing. This initiative builds on a previous deployment at the Spartanburg plant in United States, where valuable experience was gained and is now being used to refine and scale the technology.

Artificial intelligence is already embedded throughout the BMW production system, underpinning functions such as digital twins, AI-supported quality assurance and autonomous transport in intralogistics. A unified data architecture serves as the foundation for this intelligence, enabling real-time access to consistent and standardised information across all manufacturing locations. This infrastructure supports the deployment of digital AI agents capable of autonomous decision-making in complex environments. When these agents are paired with robotic systems, they give rise to Physical AI, which represents a significant evolution in production technology.

The company views humanoid robotics as a strategic addition to its automation portfolio. These robots are particularly suited to tasks that are repetitive, physically strenuous or present safety risks. By deploying them in such roles, the company aims to reduce physical strain on employees and enhance workplace conditions. To drive this forward, a Center of Competence for Physical AI in Production has been established to consolidate expertise and facilitate knowledge sharing across the organisation.

A structured process governs the evaluation of potential technology partners. Candidates are assessed against criteria related to maturity and industrial applicability, followed by laboratory testing using real production scenarios. Successful tests lead to limited deployments under actual factory conditions before advancing to full pilot phases. This methodology ensures that only thoroughly vetted solutions are integrated into series production.

The Leipzig pilot is being conducted in collaboration with Hexagon, a longstanding partner specialising in sensor technology and software. Following theoretical and laboratory evaluations, an initial deployment of Hexagon’s humanoid robot, AEON, took place at the plant in December 2025. A second test phase is scheduled for April 2026, with the full pilot set to begin in the summer of that year. The robot’s human-like design allows for the attachment of various tools and grippers, making it adaptable for multiple tasks in battery assembly and parts manufacturing.

Earlier work at the Spartanburg plant provided critical insights into the practical application of humanoid robotics. In partnership with Figure AI, the robot Figure 02 was deployed in body shop operations, where it handled the precise placement of sheet metal parts for welding. Over 10 months, the robot supported the production of more than 30,000 vehicles, operating in 10-hour shifts and handling over 90,000 components. The pilot demonstrated that humanoid robots could perform high-precision tasks reliably and safely in a live production setting. It also highlighted the importance of early collaboration with teams responsible for IT infrastructure, safety and logistics. Seamless integration into the existing automation ecosystem was achieved through standardised interfaces, and employee reception was notably positive, aided by transparent communication from the outset.

The success of these initial deployments has paved the way for further collaboration. BMW and Figure are currently exploring additional applications for the next-generation Figure 03 robot, continuing to build on the foundation established in both United States and Europe.

Milan Nedeljković, Member of the Board of Management of BMW AG, Production, said, “Digitalisation improves the competitiveness of our production – here in Europe and worldwide. The symbiosis of engineering expertise and artificial intelligence opens up entirely new possibilities in production,”.

Michael Nikolaides, Senior Vice President Production Network, Supply Chain Management at BMW Group, said, “Our aim is to be a technology leader and to integrate new technologies into production at an early stage. Pilot projects help us to test and further develop the use of Physical AI – that is, AI‑enabled robots capable of learning – under real-world industrial conditions. The successful first deployment of humanoid robots at our BMW Group plant in Spartanburg in the USA proves that a humanoid robot can function not only under controlled laboratory conditions but also in an existing automotive manufacturing environment.”

Michael Ströbel, Head of Process Management and Digitalisation, Order to Delivery at BMW Group, said, “We are delighted to deploy a humanoid robot for the first time in a pilot project at a plant in Germany. Following evaluation by our Center of Competence for Physical AI in Production, tests were carried out in the laboratory and at Plant Leipzig at the end of last year. This year, our focus is on step‑by‑step integration into our production system to explore a wide range of applications. The emphasis is on researching multifunctional use of the robot in various production areas such as battery manufacturing for energy modules and component production for exterior parts. With Hexagon, we have found a proven long‑standing partner with a highly innovative approach to humanoid robotics for this project.”

Felix Haeckel, Team Lead CoC Physical AI for Production, said, “At our new Center of Competence for Physical AI in Production, we are pooling our expertise to make knowledge on AI and robotics widely usable within the company. In recent years, we have built up an international team of experts that, in addition to in‑house research and programming, is dedicated to the gradual integration of AI into the existing production system. At the same time, our team in Munich is driving its own robotics research to set up, support and further develop pilot projects in the field of Physical AI at our plants.”

Arnaud Robert, President of Hexagon Robotics, said, “We are very pleased to be working with the BMW Group to advance the use of humanoid robots in real‑world environments.”

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Pre-owned car marketplace Cars24 has announced the launch of AI Labs, a dedicated initiative designed to develop artificial intelligence-native products and support early-stage entrepreneurs.

As part of the program, the company has committed a USD 20 million investment fund targeted at startups and development teams building transformative AI technologies.

The move marks an expansion of Cars24’s internal technology strategy, where machine learning and artificial intelligence models have already been integrated into core business operations to manage decision-making workflows and customer experience interfaces. Through AI Labs, the company will extend its technical resources externally to independent software engineers and startup founders.

To establish the infrastructure for the program, Cars24 has partnered with technology providers including OpenAI, Amazon Web Services (AWS) and ElevenLabs. This ecosystem will provide participating developers with cloud infrastructure, technical expertise, distribution networks and advanced language and voice synthesis models to accelerate product deployment.

The operational focus of AI Labs is divided into three primary activities:

• Build: Developing proprietary AI-native applications and contributing to global open-source software innovation.
• Partner: Collaborating with established artificial intelligence firms to encourage industry experimentation and technology adoption.
• Invest: Supplying seed capital and strategic support to early-stage businesses building software categories.

Beyond direct equity investments, the initiative will fund community engagement programs, including regional hackathons, builder incubation programs and collaborative open-source projects designed to stimulate developer experimentation.

Vikram Chopra, Founder and CEO, Cars24, said, “Every major technology shift creates a handful of companies that go on to define the future. We believe AI is the biggest shift of our generation, and the opportunity ahead is far larger than anything we've seen before. Over the last few years, we've seen AI fundamentally change how we operate, build products, and serve customers AI Labs is our way of giving back to the ecosystem that is shaping this future. We want to back founders early, help them move faster and support the people building things that seem impossible today but inevitable tomorrow.”

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Automotive supplier Valeo and Electronic Design Automation software provider Zuken have announced a strategic partnership to develop an open, artificial intelligence-assisted electronic design platform. The collaboration will operate under a joint program named the ‘Zuken Valeo InnoLab’.

The initiative integrates Zuken's AI architecture with Valeo’s custom AI agents and industrial data to create a real-time collaborative ecosystem between software tools and engineers. The primary objective of the program is to reduce hardware design timelines while maintaining structural robustness across complex automotive electronic systems.

The technical development framework spans the entire electronic design flow and is organised into four main operational areas:

• Functional Generative Design: Valeo will deploy its generative AI models within Zuken’s System Planner software to instantly generate and evaluate multi-criteria system architectures based on predefined corporate standards.
• Digital Continuity: Zuken’s open architecture will interface with Valeo’s existing digital ecosystem to provide end-to-end data traceability. This integration is designed to comply with the Automotive SPICE 4.0 (ASPICE4.0) Hardware Engineering process group standard, allowing Valeo's AI to process data and execute automated actions directly within the platform.
• Assisted Detailed Design: Valeo will integrate virtual AI copilot agents to assist engineering teams in real time with hardware rule verification, solution searching, and constraint implementations. Concurrently, Zuken is developing native AI functions to accelerate schematic entries by drawing from Valeo’s standardised components database.
• Automated Placement and Routing: Physical circuit integration will utilise Zuken’s Design Force engine, which features automated placement and routing algorithms. Valeo will use Zuken's software development kit to train the AI engine against specific automotive environmental and physical constraints to achieve correct initial executions.

Christophe Le Ligne, Vice-President – Research and Development, Valeo, said, “For Valeo, Zuken is much more than a software provider; it is a true innovation partner. The power of Zuken’s AI roadmap, combined with the exceptional openness of its architecture, allows us to hybridise our own artificial intelligence tools with their engine. This win-win partnership is the best way to tackle the challenge of automotive complexity by slashing our design times while guaranteeing 100% robustness.”

Ryosuke Takagi, Executive Officer and General Manager – R&D Division, Zuken, added, “Our vision at Zuken has always been to provide intelligent tools that adapt to our customers’ most complex challenges. Collaborating with a technological leader like Valeo pushes our ‘Autonomous Brain’ roadmap to its highest level of performance. By opening our System Planner, Design Gateway, and Design Force solutions to Valeo’s AI agents, we demonstrate that the true power of AI in engineering lies in the alliance between a high-performance software engine and expert industrial know-how.”

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Artificial intelligence software developer Helm.ai has launched two foundation models, GenSim-3 and VidGen-3, establishing a native Full HD (1920x1080) resolution standard for generative simulation across a 6-camera, 360-degree surround-view suite.

The architecture delivers 5x the pixel density of industry benchmarks to assist automotive developers facing the limitation where physical collection of edge cases becomes logistically restrictive.

Traditional generative world models typically cap resolution at roughly 0.4 megapixels per camera. Helm.ai’s platform outputs a native 2 megapixels per camera, yielding a synchronised 12-megapixel synthetic canvas per timestep. This specification matches the hardware parameters of production-grade vehicle cameras to reduce the domain gap for SAE Level 2 through Level 4 autonomous vehicle development.

The platform functions as a virtual sensor twin by mathematically replicating physical constraints and hardware anomalies, including lens flares, sensor banding patterns, and exposure blinding. To accommodate different neural network training routines, the pipeline can be configured to a high-speed validation mode using a three-camera setup at 30 frames per second, or a spatial context mode generating a six-camera surround view at 5 frames per second.

Data generation is split into two operational pipelines. GenSim-3 focuses on data augmentation by modifying environmental parameters such as weather, lighting, and object surfaces across real-world video segments at native 2MP resolution. VidGen-3 focuses on data creation, synthesising driving sequences from scratch by simulating environments, agent behaviours, and traffic logic without baseline video to patch geographic data gaps.

Helm.ai achieved the 2MP standard using a cluster of a few hundred GPUs rather than the thousands typically required for sub-HD video generation. This framework reduces the GPU infrastructure footprint for vehicle manufacturers and provides a method for compressing autonomous driving software onto mass-market on-vehicle compute chips.

Vladislav Voroninski, CEO and Founder, Helm.ai, said, "We are moving the industry from standard 'AI video' to authentic, hardware-accurate sensor emulation. By leading with a Full HD (2MP) standard and a 12-megapixel total aggregate capability per timestep, we have solved the resolution bottleneck that has historically limited the utility of generative AI in safety-critical systems. By optimising our compute architecture, we are giving our partners a high-performance platform to validate their autonomous stacks using synthetic data that perfectly matches the fidelity of their actual production sensors."

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Global automotive technology supplier Marelli has marked the 30th anniversary of its flagship electronics manufacturing plant in Guangzhou. Established in 1996 as Marelli’s inaugural manufacturing investment in China, the facility has transformed from a baseline assembly outpost into a major smart manufacturing and hardware-software validation centre.

Over the past three decades, the facility has expanded from a single operational production line with approximately 100 technicians into a 30,000-square-meter automotive electronics campus.

Today, the facility employs nearly 1,000 people and runs 66 active production lines, manufacturing components for both localised Chinese vehicle programs and global vehicle architectures.

The campus houses an adjacent, fully integrated Engineering Center that holds more than 100 registered patents. The manufacturing framework integrates high-precision assembly lines, automated optical bonding modules and site-wide rooftop solar arrays designed to manage factory energy overheads and lower operational carbon density.

The Guangzhou plant functions as a strategic industrialisation hub focused on low-cost, scalable architectures suited for the industry transition toward connected, software-defined vehicles (SDVs). The facility specialises in several high-growth hardware and display segments like advanced display solutions based on Mini-LED and MicroLED technologies. Additional key platforms include electronic control units (ECUs) for body and seat systems, zone control units, as well as digital cockpits, digital instrument clusters, and 5G telematics systems.

Ravi Tallapragada, President of Marelli’s Electronics business unit, said, “Our Guangzhou plant is a cornerstone of Marelli’s Electronics business in China and a powerful example of how innovation and advanced manufacturing can drive sustainable growth. Over the past 30 years, the team has continuously evolved its capabilities, developing advanced technologies and scalable platforms that address the rapid transformation of the automotive industry, building on long-standing collaboration with customers and partners. I’m proud of our team in Guangzhou and confident that the plant will continue to play a key role in shaping Marelli’s future globally.”

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