Rockwell Automation, the world’s largest company dedicated to industrial automation and digital transformation, is demonstrating an AI‑based manufacturing development system at the machine level that promises to reduce engineering and configuration efforts from days to minutes. By using AI to build, modify, and debug machine and process models based on engineers’ instructions, the system introduces a fundamentally different way of developing and commissioning industrial automation.

At the core of this approach is the use of an AI copilot alongside Emulate3D® digital twin software and FactoryTalk Design Studio™

a cloud‑based industrial controller engineering platform. Together, these technologies allow engineers to generate and refine controller projects based on a virtual factory model and validate them through closed‑loop digital twin testing before any physical hardware is deployed.

Using this workflow, programmable logic controller (PLC) code is created in the design platform, while the machine concepts are modeled in the digital twin virtual environment. The engineering data from this is then reused in the design platform to generate the controller code, which is then tested against the virtual model, allowing engineers to validate behavior and identify issues in a virtual environment before deployment. By moving from a validated digital machine model to a fully tested controller project, engineering and commissioning cycles can be significantly shortened.

Until now, these steps typically required multiple separate tools, along with significant manual effort for code translation, configuration duplication and test script generation to adapt controllers to real factory floor conditions. By integrating these activities into a single, AI‑based workflow, the new approach reduces complexity while lowering risk.

In addition to compressing engineering and configuration work into minutes, Rockwell Automation estimates the AI-orchestrated development system can reduce process commissioning times by up to 50%. This approach helps manufacturers improve productivity while enabling safer and more sustainable operations.

AI agents within the system can also learn from the experts they work with and then apply that knowledge to other projects. This has the potential to help new engineers become productive in minutes rather than months, while further reducing the likelihood of coding errors through digital twin–based validation.

Beyond operational efficiency, the concept delivers broader social and environmental benefits. From a social perspective, improved virtual testing helps reduce failure rates and enhance safety while addressing the global shortage of skilled automation engineers. Faster deployment of advanced manufacturing assets also supports industrial competitiveness and economic resilience.

Environmentally, the system’s virtual design and testing capabilities help reduce waste, hardware reworking and energy consumption. Fewer late‑stage changes and on‑site iterations also reduce travel requirements, while AI‑assisted optimization contributes to improved energy efficiency across industrial systems.

By combining industrial automation expertise with AI and cloud capabilities, Rockwell Automation is introducing a new engineering dynamic in which AI orchestrates the entire lifecycle: from digital factory modelling and automation logic creation to emulation, validation and continuous optimization. This enables manufacturers to unlock value much earlier in the lifecycle.

At HANNOVER MESSE 2026, Rockwell Automation will showcase this capability through an immersive extended‑reality 3D simulation of a robot‑assisted welding cell. The virtual demonstration will be presented at Rockwell Automation’s booth in the AI in Manufacturing area, Hall 27, Stand A22.

In addition, the company will highlight its AI thought leadership through dedicated sessions. Jordan Reynolds, vice president of artificial intelligence & autonomy at Rockwell Automation, will host a deep dive, titled The Future of Industrial AI: From Automation to Autonomous Operations , exploring how industrial‑grade AI enables scalable autonomy in manufacturing. Reynolds will also participate in an AI panel discussion, titled Shaping the Future of Industrial AI: Creating Value While Managing Risk as part of the AI in Manufacturing program on the center stage.