Retaining explicit and implicit knowledge with RAG-enhanced Generative AI

Abstract

Organizational knowledge, both explicit in documents and implicit in employees’ minds, is a key source of competitive advantage but is often lost through turnover and inadequate knowledge management. This study demonstrates how Generative AI (GenAI) combined with Retrieval Augmented Generation (RAG) can help retain and reuse such knowledge. Using the Design Science Research methodology, a GenAI system was developed and applied in a case study of the purchasing department of a major European engineering and technology company. The solution uses transcripts from expert debriefing interviews to elicit and categorize implicit knowledge at both surface and deep levels. The AI system interprets and contextualizes expert insights, transforming them into accessible organizational knowledge. The resulting artefact enables efficient retrieval and reuse of codified expertise and is transferable across business contexts. Workshop evaluations confirmed its effectiveness in capturing and applying implicit knowledge, demonstrating that GenAI with RAG offers a practical approach to mitigating knowledge loss and leveraging organizational expertise more effectively.