From Expert Intuition to Institutional Memory: A GenAI Augmented Knowledge Transfer Framework for Aviation MRO Organisations

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Abstract
The aviation Maintenance, Repair and Overhaul (MRO) sector faces an acute tacit knowledge continuity challenge as a generation of master technicians approaches retirement, yet existing knowledge management (KM) frameworks offer no tools calibrated to aviation's safety critical, highly regulated operating environment. Addressing this gap, this paper develops a conceptual framework: the GenAI SECI MRO Framework that integrates the SECI model of knowledge creation with emerging generative artificial intelligence (GenAI) capabilities. Following a PRISMA guided systematic literature review of research at the KM, aviation, and AI intersection, the study identifies four critical gaps and translates them into the framework's design requirements. The framework reconceptualises each SECI phase through GenAI augmented mechanisms operating within EASA/FAA regulatory compliance boundaries and embeds a regulatory validation layer as a co‐equal design constraint. Theoretically, the study extends the SECI model to high reliability organisational (HRO) contexts and draws on the resource based view (RBV) to position institutional knowledge as a strategic asset. This is a conceptual framework development study: the proposed mechanisms are theoretically grounded propositions that require empirical validation in operational MRO settings, for which a structured research agenda is provided. The framework offers KM scholars a sector specific extension of knowledge creation theory and gives MRO managers a structured roadmap for knowledge continuity.

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