Concept for acquiring implicit knowledge in industrial production: challenges, best practices and LLM based use cases

Aging workforces in western industrialized countries are leading to a growing loss of experiential knowledge, particularly on the shop floor where expertise is largely tacit and informally acquired. This HICSS presentation reports on a study that examines current challenges in industrial knowledge management and identifies promising application areas for large language models (LLMs) within a broader effort to develop human-centered, GenAI-supported KM solutions. Based on two structured workshops with 23 experts from 14 German manufacturing companies, the study reveals key barriers to knowledge retention and highlights two prioritized LLM use cases. The findings provide concrete design implications for LLM-enabled KM systems and contribute practical insights into addressing demographic change in industrial contexts.