Siemens maps AI-led industrial shift at CES, with fusion reactors highlighting digital twin strategy

Roland Busch, CEO of Siemens (right), and Bob Mumgaard, CEO of Commonwealth Fusion Systems (left), speak during a keynote session on Jan. 6 at the Venetian Hotel in Las Vegas, discussing partnership examples in which AI is driving large-scale industrial transformation. The image of a fusion power plant shown on the screen behind them depicts a virtual environment built using digital twin technology. AJP Park Sae-jin
LAS VEGAS (AJP) - At CES 2026, Siemens outlined a vision for an AI-driven restructuring of global industry, arguing that artificial intelligence is moving beyond software applications to become a foundational element of physical systems across manufacturing, logistics, energy, and infrastructure. At the center of that strategy is digital twin technology, which the company presented as the key mechanism for applying AI safely and reliably in the real world.

Siemens framed digital twins not as visualization tools but as operational replicas of physical systems. By integrating design data, operating conditions, physical laws, and real-time sensor information, digital twins allow companies to test and validate thousands of scenarios before assets are built or deployed. According to Siemens, this capability is critical in industries where errors carry high costs or safety risks, and where traditional trial-and-error approaches are impractical.

Roland Busch, president and CEO of Siemens, emphasized those constraints during his keynote on Jan. 6 at the Venetian Hotel in Las Vegas. “In the industrial world, AI hallucinations are not acceptable,” Busch said. “AI that enters physical systems is no longer just a feature. It becomes a force with direct real-world impact.” Reliability and safety, he added, are prerequisites for deploying AI at industrial scale, making digital twins a necessary foundation rather than an optional enhancement.

The company used nuclear fusion energy as its most prominent example of that approach in practice. Siemens highlighted its collaboration with Commonwealth Fusion Systems, a U.S.-based fusion startup, to demonstrate how digital twins can accelerate development in fields defined by extreme complexity and risk. Fusion reactors require precise coordination among magnets, cooling systems, and power controls, where even small design flaws can have serious consequences.

Busch said such systems leave no room for real-world experimentation. “In these environments, trial and error in the physical world is not an option,” he said. Every design choice and operating condition must be validated in a digital twin, where physical behavior can be simulated repeatedly before any hardware is built. Siemens argued that this process shortens research and development timelines while reducing the likelihood of costly or dangerous failures.

Siemens positioned the fusion work as a template rather than a one-off case. The same digital twin framework, the company said, can be applied to factories, logistics centers, and power grids. By combining virtual replicas of these systems with AI, operators can anticipate disruptions, optimize performance, and adjust operations in real time. Busch described this shift as a move away from reacting to problems after they occur toward designing systems that act proactively.

Partnerships with major technology firms were presented as critical to making that model work at scale. Siemens pointed to its collaborations with NVIDIA and Microsoft as efforts to link AI-accelerated computing, simulation technologies, and industrial AI copilots into a single workflow spanning design, manufacturing, and operations. The company also showcased hands-free, smart-glasses-based guidance for shop-floor workers, positioning it as a way to improve safety and productivity while narrowing skill gaps.

At CES 2026, Siemens focused less on individual product announcements than on defining how AI can be embedded into physical systems without compromising safety or reliability. By using fusion reactors as a proving ground for digital twin technology, the company sought to show how AI-driven simulation can reduce risk and compress development cycles in the most demanding industrial environments, before extending that same logic across manufacturing, logistics, energy, and infrastructure.
Park Sae-jin Reporter swatchsjp@ajunews.com