On the Las Vegas keynote stage at CES 2026, Siemens president and CEO Roland Busch declared that Industrial AI is no longer a feature but “a force that will reshape the next century,” drawing a direct parallel with the way electricity transformed industry in the 20th century. His message to manufacturers, infrastructure operators and city leaders was blunt: AI is moving out of the lab and into the core of how physical systems are designed, built and run.
Siemens used the keynote to argue that the winners of this transition will be those who treat AI as “native” to their operations, embedding intelligence from the first CAD model through to production lines, grids and rolling stock, rather than bolting on isolated pilots. “From the most comprehensive digital twin and AI‑powered hardware to copilots on the shop floor, we’re scaling intelligence across the physical world,” Busch said, promising simultaneous gains in speed, quality and efficiency.
Digital Twin Composer: powering an industrial metaverse
The centrepiece announcement was Digital Twin Composer, a new software product Siemens plans to launch on its Xcelerator marketplace in mid‑2026. The tool is designed to create photorealistic 3D digital twins of products, plants and processes, linking them to real‑time engineering data and machine time‑series signals so teams can test changes virtually, analyse incidents and simulate forward before touching physical assets.
Built using Siemens’ existing simulation stack and Nvidia’s Omniverse technologies, Digital Twin Composer is pitched as a way to take the “industrial metaverse” from concept to daily practice, letting engineers and operators see not just how a system looks, but how it behaves under different scenarios. Early adopter PepsiCo was highlighted as using the platform to simulate facility upgrades with the goal of catching up to 90% of issues before implementation, with plans to scale globally.
Siemens and Nvidia deepen Industrial AI OS ambitions
Siemens also used CES to expand its strategic partnership with Nvidia, with the two companies working toward what they describe as an “Industrial AI Operating System” spanning the full lifecycle of products and production. The aim is to create AI‑accelerated workflows from design and engineering through manufacturing, operations and supply chains, enabling continuous optimisation rather than sporadic improvement projects.
As part of the push, Siemens plans to integrate Nvidia NIM and Nemotron open AI models into its electronic design automation tools, bringing generative and agentic AI into semiconductor and PCB design for more accurate, domain‑specific automation at lower operating cost. The companies also flagged plans to develop fully AI‑driven adaptive manufacturing sites, starting with Siemens’ electronics factory in Erlangen, Germany, as an early blueprint.
Nine industrial copilots and AI on the shop floor
Another major theme was the rollout of nine new “industrial copilots” across Siemens’ software portfolio, developed in close collaboration with Microsoft. These AI assistants are designed less as chat interfaces and more as execution guides, embedded into environments such as Teamcenter, Polarion and Opcenter to streamline product data navigation, automate compliance documentation and orchestrate manufacturing workflows.
By operating in controlled, auditable contexts, the copilots aim to help engineers and operators follow best‑practice procedures, reduce errors and shorten ramp‑up times on new lines or products. Siemens also showcased hands‑free, AI‑driven guidance using Meta Ray‑Ban AI glasses, delivering real‑time instructions and safety insights to technicians directly on the shop floor. The company framed these tools as part of a broader push to make AI tangible for frontline workers rather than just data scientists.
From autonomous vehicles to fusion: use cases on display
Beyond factory walls, Siemens used its CES presence to demonstrate how industrial AI and digital twins are being applied in autonomous driving, drug discovery and future energy. A new PAVE360 Automotive system‑level digital twin was shown as a way to accelerate development of software‑defined vehicles, including an on‑site car operating autonomously in a fully virtual environment.
Commonwealth Fusion Systems CEO Bob Mumgaard joined the lineup to explain how Siemens technology is helping accelerate commercial fusion energy development, positioning high‑fidelity simulation and AI as key tools in tackling one of the world’s most complex engineering challenges. Siemens also highlighted work with life‑science partners, including integration with platforms such as Dotmatics, to speed up drug discovery using AI‑driven analysis and modelling.
Integration and governance: the hard work ahead
While the announcements painted an ambitious vision of end‑to‑end Industrial AI, Siemens and industry commentators repeatedly stressed that the real bottlenecks lie in integration, data governance and safety frameworks, not in demo‑ready AI models. Making digital twins “continuously updated decision layers” and copilots reliable guides for complex operations will require clean data, clear rules on what AI can recommend or automate, and robust guardrails against unsafe or opaque behaviour.
For manufacturers and infrastructure operators watching from CES, the message was two‑fold: Industrial AI is ready enough to move from pilot to platform, but only organisations that invest in the underlying plumbing—connectivity, data models, security and change management—will translate Siemens’ tech stack into fewer late‑stage design changes, shorter ramp times and repeatable operational gains. At CES 2026, Siemens made its bet clear: the next decade of industrial competitiveness will be written at the intersection of AI, automation and the digital twin.