Siemens & NVIDIA Announce Partnership at CES to Develop AI for Industrial Applications

Siemens and NVIDIA announced an expansion of their existing strategic partnership to bring artificial intelligence into the real world at the Consumer Electronics Show (CES) in Las Vegas this week. Together, the companies aim to develop industrial and physical artificial intelligence (AI) solutions that will bring AI-driven innovation to every industry and industrial workflow, as well as accelerate each others’ operations.

To support development, NVIDIA will provide AI infrastructure, simulation libraries, models, frameworks and blueprints, while Siemens says it will commit hundreds of industrial AI experts and leading hardware and software.

“Together, we are building the Industrial AI operating system — redefining how the physical world is designed, built and run — to scale artificial intelligence  and create real-world impact,” said Roland Busch, president and chief executive officer  of Siemens AG, in the press release. “By combining NVIDIA’s leadership in accelerated computing and AI platforms with Siemens’ leading hardware, software, industrial AI and data, we’re empowering customers to develop products faster with the most comprehensive digital twins, adapt production in real time and accelerate technologies from chips to AI factories.”

“Generative artificial intelligence and accelerated computing have ignited a new industrial revolution, transforming digital twins from passive simulations into the active intelligence of the physical world,” said Jensen Huang, founder and chief executive officer of NVIDIA. “Our partnership with Siemens fuses the world’s leading industrial software with NVIDIA’s full-stack artificial intelligence platform to close the gap between ideas and reality — empowering industries to simulate complex systems in software, then seamlessly automate and operate them in the physical world.”

Siemens and NVIDIA will work together to build AI-accelerated industrial solutions across the full lifecycle of products and production, enabling faster innovation, continuous optimization and more resilient, sustainable manufacturing. The companies aim to build the world’s first fully AI-driven, adaptive manufacturing sites globally, starting in 2026 with the Siemens Electronics Factory in Erlangen, Germany, as the first blueprint.

Using an “AI Brain,” — powered by software-defined automation and industrial operations software, combined with NVIDIA Omniverse libraries and NVIDIA AI infrastructure, factories can continuously analyze their digital twins, test improvements virtually and turn validated insights into operational changes on the shopfloor. This results in faster, more reliable decision-making from design to deployment — raising productivity while reducing commissioning time and risk. The companies aim to scale these capabilities across key verticals and several customers are already evaluating some of the capabilities including Foxconn, HD Hyundai, KION Group and PepsiCo.

With the partnership expansion, Siemens will complete GPU acceleration across its entire simulation portfolio and expand support for NVIDIA CUDA-X libraries and AI physics models, enabling customers to run larger, more accurate simulations faster. Building on that foundation, the companies will advance toward generative simulation by using NVIDIA PhysicsNeMo and open models to provide autonomous digital twins that deliver real-time engineering design and autonomous optimization. 

By applying industrial AI operating logic to semiconductors and AI factories, Siemens and NVIDIA will accelerate the engines of the revolution. Starting with semiconductor design and building on NVIDIA’s extensive use of Siemens’ tools, Siemens will integrate NVIDIA CUDA-X libraries, PhysicsNeMo and GPU acceleration across its EDA portfolio with a focus on verification, layout and process optimization — to target 2-10x speedups in key workflows.

The partnership will also add AI-assisted capabilities such as layout guidance, debug support and circuit optimization to boost engineering productivity while meeting strict manufacturability requirements. Together, these capabilities will advance AI-native engines for design, verification, manufacturability and digital-twin approaches to shorten design cycles, improve yield and deliver more reliable outcomes.