Building an industrial AI platform

Siemens and NVIDIA have announced a significant expansion of their strategic partnership to bring artificial intelligence (AI) into practical industrial production. The collaboration focuses on developing industrial AI and physical AI solutions, promoting AI-driven innovation across all sectors and industrial processes, while optimizing operations for both companies through digital twins and accelerated computing technologies.

The expanded strategic partnership aims to advance the application of AI in real-world industrial settings. Both parties intend to jointly develop industrial and physical AI solutions, fostering innovation and accelerating operations across industries.

To support this development, NVIDIA will provide AI infrastructure, simulation libraries, models, platforms, and design templates, while Siemens will mobilize hundreds of industrial AI experts alongside leading hardware and software systems.

Roland Busch, chairman and CEO of Siemens AG, emphasized the importance of building an AI operating system for industry to scale AI capabilities and achieve tangible impacts. He noted that by combining NVIDIA’s leading position in accelerated computing and AI platforms with Siemens’ strengths in hardware, software, industrial AI, and data, Siemens enables customers to develop products faster with the most comprehensive digital twins, adapt production in real time, and accelerate technologies from chips to AI-powered factories.

Meanwhile, Jensen Huang, founder and CEO of NVIDIA, said: “Generative AI and accelerated computing have sparked a new industrial revolution, transforming digital twins from passive simulation tools into active intelligence of the physical world. Our partnership with Siemens combines the world’s leading industrial software with NVIDIA’s comprehensive AI platform, bridging the gap between ideas and reality, allowing industries to simulate complex systems in software before automating and operating them seamlessly in the physical world.”

Towards AI-powered factories and optimized production cycles

Siemens and NVIDIA will collaborate on AI-accelerated industrial solutions covering the entire product lifecycle and manufacturing process. The aim is to drive faster innovation, continuous optimization, and the establishment of sustainable and flexible production platforms. The companies plan to build the world’s first fully AI-operated adaptive factory, starting in 2026 with Siemens’ Electronics Factory in Erlangen, Germany, as a model prototype.

Using the “AI brain,” powered by software-defined automation and industrial operations management software combined with NVIDIA Omniverse libraries and NVIDIA AI infrastructure, factories can continuously analyse digital twins, test improvements in virtual environments, and convert validated information into direct operational adjustments on the shop floor.

This process enables faster and more reliable decision-making from design to deployment, enhancing productivity while reducing trial time and risks. Siemens and NVIDIA aim to expand these capabilities across key sectors, with companies such as Foxconn, HD Hyundai, KION Group, and PepsiCo currently evaluating these features.

With the partnership expansion, Siemens will complete GPU acceleration across its simulation portfolio and extend support for NVIDIA CUDA-X libraries and AI physical models, enabling customers to conduct larger, more precise simulations at higher speeds. Building on this foundation, the two companies will move towards generative simulations using NVIDIA PhysicsNeMo and open models, providing autonomous digital twins for real-time engineering design and automated optimization.

By applying industrial AI operational logic to semiconductor production and AI-powered factories, Siemens and NVIDIA aim to accelerate core engines of the AI revolution. Starting from semiconductor design, with NVIDIA extensively using Siemens’ tools, Siemens will integrate NVIDIA CUDA-X libraries, PhysicsNeMo, and GPU acceleration across its full EDA portfolio, focusing on verification, layout, and process optimization, targeting 2 - 10 times acceleration for key workflows.

The partnership also incorporates AI-assisted features such as layout guidance, debugging support, and circuit optimization, boosting engineering productivity while meeting strict manufacturing requirements. These capabilities collectively advance AI-native tools for design, verification, manufacturing readiness, and digital twin methodologies, shortening design cycles, improving success rates, and delivering more reliable outcomes.

Siemens and NVIDIA will jointly develop a scalable model for the next-generation AI factory, accelerating the industrial AI revolution and providing a high-performance platform for AI-accelerated industrial solutions from both companies.

The model will balance the power, cooling, and automation requirements of next-generation high-density computing, while ensuring technology optimization in speed and efficiency, thereby optimizing the entire lifecycle from planning and design to deployment and operation.

This joint effort connects AI platform roadmaps, AI infrastructure expertise, partner ecosystems, and accelerated simulation capabilities via NVIDIA Omniverse with Siemens’ strengths in electrical infrastructure, electrification, grid integration, automation, and digital twins. The companies aim to accelerate deployment, improve energy efficiency, and enhance sustainable operations for industrial-scale AI infrastructure globally.

Siemens and NVIDIA plan to accelerate each other’s operations and solution portfolios by implementing technologies within their own systems before expanding across industries. NVIDIA will evaluate Siemens’ solutions to streamline and optimize its operations and products, while Siemens will review workloads and collaborate with NVIDIA to accelerate performance and integrate AI into its customer offerings. By mutually driving improvement and optimizing internal systems, Siemens and NVIDIA are creating concrete evidence of value and scalability in practical industrial production.