Glossary · AI engineering and governance
Industrial AI
Also known as: AI in manufacturing, Industrial artificial intelligence
German: Industrielle künstliche Intelligenz
Industrial AI is the application of artificial intelligence methods, mainly machine learning, to industrial products, machines and processes, such as quality inspection, predictive maintenance, process optimization, robotics and engineering support, under the reliability, safety and lifetime requirements of industrial environments.
- Industrial AI
- AI
In one sentence
Industrial AI applies machine learning and other AI methods to machines and processes under industrial reliability and safety requirements.
Example
Industrial AI applications in a plant include camera-based defect detection, energy forecasting and an assistant that searches maintenance manuals.
How it applies
- Engineering: Industrial AI differs from consumer AI in its constraints: limited labeled data, long equipment lifetimes, integration with PLCs and MES, and the need for traceable, validated behavior.
- Compliance: Depending on its function, an AI system in a machine or product may fall under the EU AI Act and product legislation such as the Machinery Regulation. Classification depends on the intended purpose, not on the technology alone.
- Documentation: Users need to know where AI is used, what it does, its limits and what to do when its output seems wrong. Documentation teams also use AI themselves (AI-assisted documentation).
Industrial AI vs. generative AI
Much industrial AI consists of specialized models for classification, prediction or optimization. Generative AI creates text, images or code and is used in industry mainly for engineering support, documentation and assistance systems.