Intergenerational Tacit Knowledge Transfer: Leveraging AI

Bettina Falckenthal (), Manuel Au-Yong-Oliveira and Cláudia Figueiredo
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Bettina Falckenthal: Department of Mechanical Engineering, Doctoral School, University of Aveiro, 3810-193 Aveiro, Portugal
Manuel Au-Yong-Oliveira: Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), Research Unit on Governance, Competitiveness and Public Policies (GOVCOPP), Department of Economics, Management, Industrial Engineering and Tourism (DEGEIT), University of Aveiro, 3810-193 Aveiro, Portugal
Cláudia Figueiredo: Centro de Investigação de Políticas do Ensino Superior (CIPES), Departamento de Ciências Sociais, Políticas e do Território (DCSPT), University of Aveiro, 3810-193 Aveiro, Portugal

Societies, 2025, vol. 15, issue 8, 1-22

Abstract: The growing number of senior experts leaving the workforce (especially in more developed economies, such as in Europe), combined with the ubiquitous access to artificial intelligence (AI), is triggering organizations to review their knowledge transfer programs, motivated by both financial and management perspectives. Our study aims to contribute to the field by analyzing options to integrate intergenerational tacit knowledge transfer (InterGenTacitKT) with AI-driven approaches, offering a novel perspective on sustainable Knowledge and Human Resource Management in organizations. We will do this by building on previous research and by extracting findings from 36 in-depth semi-structured interviews that provided success factors for junior/senior tandems (JuSeTs) as one notable format of tacit knowledge transfer. We also refer to the literature, in a grounded theory iterative process, analyzing current findings on the use of AI in tacit knowledge transfer and triangulating and critically synthesizing these sources of data. We suggest that adding AI into a tandem situation can facilitate collaboration and thus aid in knowledge transfer and trust-building. We posit that AI can offer strong complementary services for InterGenTacitKT by fostering the identified success factors for JuSeTs (clarity of roles, complementary skill sets, matching personalities, and trust), thus offering organizations a powerful means to enhance the effectiveness and sustainability of InterGenTacitKT that also strengthens employee productivity, satisfaction, and loyalty and overall organizational competitiveness.

Keywords: tacit knowledge; artificial intelligence (AI); intergenerational teams; knowledge transfer (search for similar items in EconPapers)
JEL-codes: A13 A14 P P0 P1 P2 P3 P4 P5 Z1 (search for similar items in EconPapers)
Date: 2025
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