By Peter Welander for Mouser

Published September 2, 2026

Artificial intelligence (AI), and more specifically generative AI (GenAI), is becoming common in everyday life. Those same technologies are starting to find a place in industrial automation, as well. Large language models (LLMs) are critical to this development because they allow people to interact with complex information using ordinary language. To understand what that could mean on the factory floor, it helps to start with a simple explanation of how they work.

LLMs are deep learning models trained on enormous collections of text. During training, they learn statistical relationships among words and other pieces of language, which allows them to recognize patterns and generate responses based on context. Ask an LLM to write a love poem, for example, and it will not retrieve a poem it has seen before. Instead, it generates new text based on patterns learned during training. The same basic capability allows an LLM to summarize a technical document, explain a piece of software code, answer questions about information it has been given, or help turn written requirements into programming instructions.

Those capabilities open up interesting possibilities for industrial automation. Manufacturing environments generate enormous amounts of information, from operating records and maintenance histories to engineering documentation and control code. Engineers and operators must find, interpret, and act on that information. An LLM provides a new way to interact with it, potentially reducing some of the work required to move from a question or engineering requirement into useful technical information.

What might that look like in practice? This article addresses that question by examining two hypothetical examples: an oil refinery and a packaging line.

>>Read the entire article at Mouser

About the Author

Peter Welander has been working as a freelance writer and editor for more than 10 years, following seven years as a senior editor and content manager for Control Engineering magazine. During this time he has written heavily about industrial automation, primarily in process industries. He has also worked on audio and video production, podcasts, and blogging. Peter moved into the publishing world following many years working in sales and marketing management, engineering, and operations for a variety of industrial manufacturers. One capability that he has had throughout his career is the ability to grasp technical concepts and explain complex ideas clearly. His personal interests include photography, a machine shop, woodworking, and pipe organ building.