Artificial intelligence and machine learning technologies are impacting automation in exciting, novel ways. This was the primary takeaway from Jordan Reynolds' press conference on November 19 at Automation Fair 2025, titled The AI Playbook: What's Needed for Transformative Change. Reynolds, Vice President of AI at Rockwell Automation, was eager to share how AI-powered solutions are becoming a core feature of their offerings.

“AI isn’t a new product line for us,” Reynolds explained. “Instead, it’s a transformative enhancement that improves the performance of our existing solutions in design, sensing, control, operations, and maintenance.”

Deploying AI/ML for QC/QA

At Automation Fair, Rockwell introduced its first QC/QA machine vision solution, VisionAI. VisionAI eliminates rule-based programming and instead relies on machine learning. Operators provide the system with database examples of specimen tolerance, which improve over time as corrections are applied. For applications without historical references, digital twin simulations of the environment can provide insights into key specifications or anomalies.

AI for Simulation and Generation

This naturally leads to the Studio5000 programming environment and Emulate3D simulation software. AI expedites workflows and identifies engineering efficiencies, offering critical technical understanding.

Generative AI allows engineers to program and write code using natural language instructions. This includes generating test scripts, adding comments, and performing syntax and safety validations. With Emulate3D, engineers can simulate and validate automation systems before deployment. This digital sandbox allows users to create and refine AI-driven production systems without relying on historical data.

Predictive Maintenance Goes Native

The GuardianAI platform is enhancing predictive maintenance strategies. It offers maintenance analysis without additional sensors, such as vibration or temperature sensors, by monitoring motor current signals against an established baseline. FIX, an AI-enhanced maintenance management system, triggers work orders, scheduling recommendations, and inventory requisitions. This approach enables predictive maintenance without the need for new hardware.

Optimizations for operations

PLCs are also getting an upgrade. Rockwell’s Logix AI machine learning enables ControlLogix PLCs to learn and adapt dynamically to control processes. The Pavilion product uses neural network technology to model and optimize nonlinear, multivariable processes. Pavilion was one of the earliest adopters of neural networks in automation.

Rockwell’s AI enhancements extend to its MES platforms, Plex and Production Center, with AI-powered features for production planning, resource allocation, and scheduling. Using AI to solve these complex problems can increase throughput by up to 10%.

Although many AI models are hosted on the cloud, edge AI also plays a role. HMIs are increasingly running models to provide real-time, machine-level insights, boosting responsiveness and efficiency.

Future-Focused AI

“Our goal is to provide engineers with tools that not only simplify their work but also deliver smarter, faster, and more reliable results,” Reynolds said.

This aligns with Rockwell's philosophy to enable low-cost, AI-driven automation without requiring deep programming knowledge, steep learning curves, or significant investments. Companies with an integrated strategy will find new opportunities for productivity, efficiency and ultimately, profitability.

To contact the author of this article, email kharrigan@globalspec.com