Industrial Artificial Intelligence (AI) refers to the application of AI technologies specifically to industry and business challenges, differing from general AI research by focusing on creating customer value, improving productivity, and reducing costs. Its recent surge is powered by factors like more affordable sensors, enhanced computing power, and accessible cloud services, which together facilitate leveraging vast amounts of production data.

Industrial AI boasts diverse applications across seven key areas, including market analysis, machinery and equipment (e.g., predictive and preventive maintenance), intralogistics, and optimizing production processes (e.g., collaborative robots). However, its adoption faces significant hurdles, primarily due to the intricate interaction between virtual and physical production systems, alongside the high reliability requirements and potential economic risks involved. Further challenges stem from the conservative nature of the production industry, the complexity of heterogeneous and often information-sparse data, and a notable lack of IT and data science expertise within the domain.