AI agents for industrial automation mark fundamental shift
Siemens is developing AI agents to work with its established Industrial Copilots and creating a marketplace for third party agents.
This marks a fundamental shift from AI assistants that respond to queries towards truly autonomous agents that proactively execute entire processes without human intervention.
The AI agent architecture uses an orchestrator that deploys a toolbox of specialized agents to solve complex tasks across the entire industrial system, working autonomously. These agents understanding intent, improve performance through continuous learning and access external tools and other agents as needed. Users retain complete control, selecting which tasks they wish to delegate to AI agents.
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Siemens’ approach distinguishes between Industrial Copilots, the interfaces users interact with, and the AI agents. It is also developing digital agents and integrating physical agents, including mobile robots. This creates a multi-AI-agent system where agents are highly connected and work collaboratively.
“With our Industrial AI agents, we’re moving beyond the question-answer paradigm to create systems that can independently execute complete industrial workflows,” said Rainer Brehm, CEO Factory Automation at Siemens Digital Industries. “By automating automation itself, we envision productivity increases of up to 50% for our customers – fundamentally changing what’s possible in industrial operations.”
Siemens is planning to create an industrial AI agent marketplace hub on the Siemens Xcelerator Marketplace. This will enable customers to access not just Siemens’ own AI agents but also those developed by third parties.
These sit alongside the copilots that are also being developed.
The Design Copilot currently available for NX CAD helps users accelerate the product design process. Design engineers can navigate complex data, balance trade-offs, and perform multi-domain tasks more efficiently. The AI-powered assistant enables users to ask questions in natural language, quickly access detailed technical insights, and streamline complex design tasks – all leading to significant efficiency gains in product development.
Siemens is also currently developing a Hydrogen Configurator for designing hydrogen production plants. Users can generate block flow diagrams with precise plant unit layouts and interconnections with it.
- A Planning Copilot is currently in pre-release with customer testimonials already available, this solution optimizes production planning, resource allocation, and scheduling through generative AI-powered insights, helping manufacturers maximize efficiency and minimize waste.
- The Engineering Copilot enables engineering without repetitive tasks. This first generative AI-powered product for automation engineering generates automation code through natural language inputs, speeding up SCL code generation while minimizing errors.
- A Maintenance Copilot provides maintenance teams with equipment diagnostics without the need for specialized technical knowledge. This has been expanded beyond predictive maintenance to cover the entire maintenance lifecycle to support everything from reactive repairs to predictive and preventive strategies, with pilot implementations demonstrating an average 25% reduction in reactive maintenance time.
- At the machine level, Siemens is planning to introduce an Operations Copilot for shop floor workers, which will be available by the end of 2025. This helps shop floor operators, service technicians, and maintenance engineers to work more efficiently by querying machine data and receiving error resolution guidance through natural language. The Operations Copilot can be easily implemented at the machine level to provide machine instructions and operator guidance.
- For the process industries, the generative AI-based assistant Simatic eaSie, enables technicians and maintenance personnel to access relevant plant and equipment data via chat or voice interaction. This makes operations and maintenance more reliable and safer both in the control room and in the field.
At thyssenkrupp Automation Engineering, where the technology is being rolled out globally, engineers have reported improvements in code quality and development speed. Meanwhile, at Siemens’ Bad Neustadt site, the Insights Hub Production Copilot has turned scattered data into actionable insights.
“In a factory environment, our Industrial AI agents connect different copilots and automate workflows across the entire value chain. This creates a unified approach that makes industrial AI accessible to everyone, regardless of their technical background or experience level,” said Brehm. “We envision a future where Industrial AI agents work seamlessly alongside human workers, handling routine processes independently while enabling humans to focus on innovation, creativity, and complex problem-solving.
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