Towards Human-Centered Learning: AI-Supported Skill Management in a Large Automotive Organization

Abstract

The use of AI in skill management has the potential to support personalized e-learning processes by identifying future skills, revealing skill gaps, and linking them to learning opportunities. At the same time, designing an AI-supported skill management system that is leveraging these potentials presents organizations with challenges. To investigate this design process, we conducted a qualitative case study based on 17 interviews and observations carried out during the pilot implementation of such a system. The case illustrates that AI-supported skill management does not automatically enable human-centered learning, but depends on balancing AI potentials, skill governance processes, and individual learning experiences. In this context, AI can be used to provide orientation in identifying future skills and deriving personalized learning impulses. This is accompanied by a reconfiguration of roles, responsibilities, and control, which are distributed across a shared sociotechnical governance structure.