Siemens introduces AI agents for industrial automation

Productivity aimed to increase by up to 50% for industrial companies.

At Automate 2025 in Detroit, Siemens is introducing enhancements to its industrial AI portfolio with new AI agents integrated into its Industrial Copilot ecosystem. These agents are designed to move beyond traditional query-based assistants by performing complete tasks autonomously. The updated AI agent framework includes an orchestrator that coordinates multiple specialized agents to handle complex operations across the industrial value chain. These agents can interpret user intent, adapt through ongoing learning, and collaborate with external tools or other agents. Users maintain control by choosing which tasks to assign to the AI agents.

Automating automation: how the AI agent architecture works

Siemens’ approach separates Industrial Copilots—the user-facing interfaces—from the AI agents that operate behind the scenes. The company is also developing digital agents and incorporating physical ones, such as mobile robots, to build a multi-agent system where different agents can coordinate tasks. This system is designed to support integration across both Siemens and third-party agents, with a focus on interoperability and cohesive operation within a broader ecosystem.

To further accelerate adoption and innovation, Siemens is planning to create an industrial AI agent marketplace hub on the Siemens Xcelerator Marketplace. This marketplace will enable customers to access not just Siemens’ own AI agents but also those developed by third parties.

The all-encompassing Siemens Industrial Copilot 

The Siemens Industrial Copilot, enhanced by Industrial AI agents, addresses every phase along the industrial value chain, across process and discrete industries:

• Design Copilot: Currently available for NX CAD, the AI-powered assistant is designed to support the product design process by helping engineers manage complex data, evaluate trade-offs, and perform tasks across multiple domains more efficiently. It allows users to ask questions in natural language, retrieve technical information, and simplify complex design activities. Siemens is also developing a Hydrogen Configurator to assist in designing hydrogen production plants, enabling users to create block flow diagrams with accurate layouts and unit connections.
• Planning Copilot: 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.
• Engineering Copilot: Available in TIA Portal, with a managed service planned for 2025, this tool streamlines automation engineering by reducing repetitive tasks. As the first generative AI-based product for this field, it allows engineers to create automation code using natural language, helping to accelerate SCL code development and reduce errors. In process industries, a copilot for P&ID digitalization is being tested by several users. This cloud-based AI service helps detect and convert legacy P&ID diagrams into digital formats. 
• Operations Copilot: Currently available for Insights Hub, the Copilot offers insights into overall plant operations. Siemens also plans to release an Operations Copilot by the end of 2025, aimed at supporting shop floor personnel such as operators, service technicians, and maintenance engineers. The tool will allow users to query machine data and receive guidance on resolving issues using natural language. It can be deployed directly at the machine level to assist with instructions and operational support. For process industries, the Simatic eaSie assistant enables access to plant and equipment data through chat or voice, supporting operations and maintenance tasks both in the control room and in the field.
• Services Copilot: The Maintenance Copilot Senseye provides maintenance teams with expert-level equipment diagnostics without the need for specialized technical knowledge. Recently expanded beyond predictive maintenance to cover the entire maintenance lifecycle, this solution supports everything from reactive repairs to predictive and preventive strategies, with pilot implementations demonstrating an average 25% reduction in reactive maintenance time.

Addressing the skills gap in manufacturing

The Siemens Industrial Copilot is in use at Siemens facilities and customer sites worldwide. At thyssenkrupp Automation Engineering, where the technology is being deployed globally, engineers have noted improvements in code quality and development time. At Siemens’ Bad Neustadt facility, the Insights Hub Production Copilot is being used to organize and interpret production data to support decision-making in manufacturing operations. 

For more information about the Siemens Industrial Copilot ecosystem and Industrial AI agents, visit siemens.com/industrial-copilot.