Agentic AI marks the shift from systems that advise to systems that execute, unlocking real, measurable value in industrial environments. Amid the growing hype around agentic AI, however, real industrial use cases are just beginning to surface.
At Hannover Messe 2026 on April 20, Siemens launched its Eigen Engineering Agent, a purpose-built AI for automation engineering designed to execute engineering tasks autonomously by applying multi‑step reasoning and self‑correction, moving beyond suggestion‑based AI tools.
With faster innovation cycles, the Eigen Engineering Agent lets engineers concentrate on higher‑level problems. “Eigen is a truly agentic technology. Consider it as your junior programmer that you essentially delegate your grunt work to — it relieves senior automation engineers to focus on the real design and tackle more advanced projects in less time,” said Girish Arunagiri, Senior Principal Product Manager at Siemens, as he demoed the agentic AI at Siemens’ booth.
Unlike generic AI tools, the Eigen Engineering Agent operates inside real engineering systems, with full awareness of each project’s context and constraints. With this understanding, it is able to execute automation engineering tasks like PLC coding, human-machine-interface (HMI) visualization, and device configuration, while meeting industrial standards for correctness and safety.
“When it comes to PLC programming, there is the logic that you need to write, keeping in mind the guidelines that your customers may impose,” said Arunagiri. “The engineers write the logic but, for example if the customer is in the automotive industry, they need to send the code back to the automotive manufacturer to comply with their guidelines.”
To minimize risk, automation engineers need tools that understand their project context and conform to their organization’s specific standards. Using the naming convention guideline example, Arunagiri explained further: “If an engineer used a naming guideline but that naming convention has changed and now you have got over 100 devices, the engineer would have to go back in and change every one of those manually. With Eigen, however, you could simply say: ‘go change all the switches to follow the naming convention.’ So, essentially, we take a lot of the grunt work out of our users’ hands and make it really easy to complete the task.
According to Siemens, the Eigen Engineering Agent completes AI-powered workflows two to five times faster than manual alternatives, with up to 80 percent higher solution quality and 50 percent greater engineering efficiency.
Another advantage, added Arunagiri, is that the Eigen Engineering Agent seamlessly connects to Siemens’ Totally Integrated Automation engineering platform (TIA Portal), giving it full context for each project. “When designing your HMI screens,” said Arunagiri, “today, you could use TIA portal to drag and drop systems controllers, and manually ensure consistency across multiple linked screens. With Eigen, you can upload an HMI style guide, and the system generates screens based on your prompt and the project context along with the guidelines defined by that guide.” It references the project’s data structures, blocks, parameters, and component relationships, so it can deliver outputs tailored to what engineers are actually building.
This contextual understanding also transforms onboarding. A large automotive line builder found that new engineers spent weeks learning project structure and component relationships before they could contribute. With the Eigen Engineering Agent, new team members could query the project directly. A request like “show me all blocks controlling Station 3” returned an immediate, accurate response. As a result, onboarding time dropped from weeks to days.
“It’s really user-friendly and a user can control what documents get added to a project,” said Arunagiri. Before presenting results to the engineer, the Eigen Engineering Agent validates all outputs. It breaks down complex tasks, executes them step by step, evaluates its own performance against the project's requirements, and iterates until the work is ready for review.
China-based CASMT, which builds high-end equipment production lines for new energy vehicles, tested Eigen Engineering Agent, and, according to Dr. Kevin Firouzian, Head of Global Strategy & Partnerships at CASMT, it helped accelerate time to market by automating device configuration, code generation, and HMI visualization.
“For our EMB (electromechanical braking) line, the Eigen Engineering Agent transformed a complex, multidiscipline challenge into a conversational workflow. It simplified setup, reduced specialist handoffs, accelerated delivery, and made debugging significantly faster,” said Firouzian.
According to Arunagiri, Siemens has piloted the Eigen Engineering Agent with more than 100 customers, and the feedback has been very positive. “We want to shape our roadmap based on customer input and continue removing friction from their workflows,” Arunagiri said. “We also want to hear what customers want us to tackle next — it could include integration further upstream from where we are today.”
This article was written by Chitra Sethi, Editorial Director, SAE Media Group. For more information, visit www.siemens.com/eigen-engineering-agent .
