Training

The governance of generative artificial intelligence (GenAI) usage is often described as a formalized reporting system. This neglects the early-stage mechanisms of coping with ethical challenges during the GenAI implementation period. Exploratory empirical findings from the Ruhr area reveal that managerial communicative practices serve as a substitute for missing institutional structures, particularly at an early stage of GenAI implementation in SMEs.

Artificial intelligence (AI) is changing the world of work. But how can work teams learn to use AI support in a way that delivers speed advantages and ensures consistently high quality? One possible approach is to test it in a workplace-like simulation. Trying it out under realistic conditions shows the role that critical thinking plays.

Designing adaptations in AI-based work systems poses a central challenge for achieving human-centered AI (HCAI). This paper presents a methodical approach that enables transdisciplinary teams to systematically explore and structure the design space of adaptable work systems. Building on an extended work system model and operationalized through a matrix-based framework, the method supports the identification of interdependencies, stakeholder perspectives, and context-specific goals. Its practical applicability is demonstrated through a real-world case study in radiographic non-destructive testing.

Demographic change is exacerbating the shortage of labor and skilled workers in the manufacturing industry, making knowledge management an increasingly important issue in many companies. Collecting and preserving tacit knowledge poses a particular challenge. This study examines the extent to which large language models (LLMs) can provide meaningful support in knowledge gathering through expert interviews. Three experts test and evaluate a personalized chatbot that has been developed using ChatGPT-5. The results of the interview are promising, but the summary shows room for improvement.

In the era of Industry 4.0, many industrial companies are facing major transformations. In the process of digitalization, factory management is adopting new technologies such as cognitive assistance systems, which has led to changes in work processes. Regarding assembly in the metal and electrical industries, it is unclear to what extent this development has promoted work-integrated learning. Therefore, the topic of this paper is a qualitative analysis that explores employees' perceptions of the learning opportunities and risks presented by cognitive assistance systems. Results: Not all assembly employees benefit equally from these new developments.

The rapid development of artificial intelligence (AI) is constantly opening new opportunities, particularly in training for the factory of the future. For employees, this not only means a significant advantage in the actual manufacturing process, but also in the field of continuing education. This paper provides an overview of AI tutoring systems continuing education in the context of Industry 4.0 by presenting a categorization that discusses different approaches of AI tutoring systems by learning methods, application areas and their respective technologies. In addition, an outlook on the disruptive effect of generative AI on AI tutoring systems in Industry 4.0 is given.

The integration of AI in Industry 4.0 is steadily increasing. Applications include both single-purpose and generative AI systems in operation practices as well as training approaches. In addition to the technical challenges posed by these systems, organizations need to assess, plan and support the organizational changes associated with technology integration.

Industry 4.0 requires new teaching content due to its innovation potential. Skills profiles currently in demand often aren't reflected in vocational and tertiary education. Additionally, conventional further education and training often costs considerably money and time. Tailor-made learning opportunities and teaching targeted problem-solving skills in a modular learning factory are a more effective approach.