The purpose of this paper is to examine the application of intelligent agents (IAs) in organizational memory systems within the larger schema of knowledge management (KM) strategies. This includes targeted roles of IAs in relation to institutional memory approaches.
A conceptual exploration of related sections of the Grundspenkis seven-layer intelligent enterprise memory framework that serves to identify, retain, deliver and reuse information for future utilization is conducted. Applications of IAs in multiple industries are presented to illustrate the conceptual model in practice.
This paper identifies arising roles that IAs perform in information search, retrieval and analysis in the organizational memory formation process and extensions that have emerged in a non-linear bi-directional form. These layered roles include obtaining and reapplying important information as part of extended human–machine cognition.
While exploratory and conceptual in nature, this research paper discusses IAs as possible components in the advancement of organization memory.
By analyzing the application of IAs in different industries, across select layers of a KM structure, groundwork is laid for both descriptive research (i.e. where and how artificial intelligence is being used in those industries) and prescriptive practice (i.e. how other industries can benefit from such assistance and what patterns of implementation to expect).
This study explores the role IAs play in helping knowledge workers gather, retain and find relevant information and how KM strategies may assist organizational memory.
Alstete, J.W. and Meyer, J.P. (2020), "Intelligent agent-assisted organizational memory in knowledge management systems", VINE Journal of Information and Knowledge Management Systems, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/VJIKMS-05-2019-0063Download as .RIS
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