Technical and Socio-Technical Success Factors of AI-Based Knowledge Management Projects

Abstract: The demographic change has a large impact on the labour market and poses a challenge to companies. With many employees going into retirement within the next 10 years, it is not just the workforce itself leaving the firms, but also their experiential knowledge that the workers gained over the years. Much of it is tacit and thus unobtainable through common documentaries of work processes. Keeping it inside of the company is crucial to ensure productivity and educate the upcoming generation of workers in their company. The project “KI_eeper – Know how to keep” has the goal to capture experiential knowledge and provide it to the workers during the production process automatically through an AI-based assistance system. The system is currently under development and requires careful consideration of the users’ needs at the production line. By choosing a participative approach, the employees are directly in touch with the developers and can influence the development of the system significantly. Managing both the available technical capabilities as well as the demands of the employees towards the system at the same time is key to have a successful outcome of the project. This paper shares the essential success factors both on the technical and socio-technical level to secure a seamless integration of an AI-based assistance system into production processes, based on a case study in a German manufacturing company.

Keywords: Artificial Intelligence, Participation, Human-centred System Design, Socio-technical approach

DOI: 10.54941/ahfe1005354

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