Siemens is looking to push factory automation far beyond current levels, with AI potentially allowing manufacturers to automate 70% to 80% of production processes, up from around 30% to 40% today. The German engineering company has said the shift could help factories in high-wage countries such as Germany remain competitive while supporting industrial jobs.
The announcement came on Monday (October 19, 2026), as Siemens showcased new AI-powered manufacturing systems at its electronics factory in Erlangen, Germany. The company is working with NVIDIA to combine AI, simulation technology, and digital twins to make production more flexible and efficient.
AI and Digital Twins Could Change Factory Operations
The partnership uses what the industry calls ‘physical AI’, combining AI models with digital twins, virtual copies of real-world equipment and production facilities. These digital replicas allow engineers to test manufacturing processes, identify potential problems, and adjust production plans before making changes on the factory floor.
At the Erlangen facility, AI-generated simulations can help train visual inspection systems before physical prototypes are available. Siemens said this approach can cut engineering effort by up to 85% and shorten time to market by up to 40%.
NVIDIA Partnership Targets Faster Production
Siemens and NVIDIA are also developing AI agents that support production planning. These systems can generate different manufacturing scenarios based on factors such as incoming orders, material availability, delivery schedules, and production capacity.
Factory planners can compare options and test them with digital simulations before implementing changes. Siemens says this approach could deliver cost savings of up to 20% while helping factories respond more quickly to supply shortages and changing customer requirements.
Also Read: Best Physical AI Development Tools and Frameworks in 2026
Siemens Invests EUR 500 Million in Its German Factory
Siemens plans to invest EUR 500 million in expanding and modernizing its Erlangen site by 2030. The facility already uses more than 100 AI algorithms across production, logistics, quality inspection, and maintenance.
The company sees the factory as a model it could replicate at other manufacturing sites. Its broader goal is to improve productivity, particularly in countries where labor and operating costs are relatively high.
However, higher automation does not automatically mean every factory will achieve the same results. The benefits will depend on production requirements, investment costs and how effectively companies integrate AI into existing operations.