Using intelligent agent technology in knowledge transfer processes according to the SECI model: A theoretical study
DOI:
https://doi.org/10.59992/IJSR.2026.v5n11p1Keywords:
Intelligent Agents, Knowledge Transfer Processes, SECI Model, Knowledge Systems in Government InstitutionsAbstract
The current study aimed to review the foreign and Arab intellectual output in the field of intelligent agent technology in knowledge transfer processes according to the SECI model, between the years (2023-2026 AD). The importance of the study lies in identifying the theoretical concepts contained in the foreign and Arab intellectual output, which helps to enrich the intellectual output in this field. This helps specialists enhance their understanding and awareness of the process of integrating concepts into research procedures, thereby fostering creativity and innovation in knowledge management processes. A documentary approach was used to review the studies. It became clear that there is a consensus among recent literature that GenAI can support socialization through conversation analysis and connecting experts, externalization through converting knowledge into texts and models, combination through RAG and integrating knowledge sources, and internalization through interactive learning.
Recent literature indicates the increasing use of artificial intelligence (AI) and generative AI in knowledge management and creation processes. Studies have also begun to re-examine the SECI model in light of the emergence of GenAI, through models such as GRAI and hybrid human-artificial knowledge models. However, most of these studies focus on GenAI in general or on specific tools like ChatGPT and RAG. There remains a need for applied research that defines the roles, types, and functions of intelligent agents at each of the four stages of knowledge transformation according to SECI, particularly within knowledge management systems in government institutions. The gap is not only in the scarcity of studies linking AI to the SECI model, however, the most specific gap is the limited number of applied studies that break down artificial intelligence into specific roles or intelligent agents, link each agent to a cognitive function and a specific stage of SECI, and then test the effect of this employment on the effectiveness of knowledge management systems within government institutions.
A clear research gap exists in both Arab and international intellectual output. However, international studies have demonstrated significant progress in the practical application of intelligent agent technologies in knowledge management, while Arab research initiatives tend to focus on each identified topic individually, often with a theoretical focus.
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