A Framework for Artificial Knowledge Creation in Organizations

Antoine Harfouche (), Bernard Quinio (), Sana Rouis Skandrani and Rolande Marciniak
Additional contact information
Antoine Harfouche: UT - Université de Tours
Bernard Quinio: CEROS - Centre d'Etudes et de Recherches sur les Organisations et la Stratégie - UPN - Université Paris Nanterre
Sana Rouis Skandrani: CEROS - Centre d'Etudes et de Recherches sur les Organisations et la Stratégie - UPN - Université Paris Nanterre
Rolande Marciniak: IDHES - Institutions et Dynamiques Historiques de l'Économie et de la Société - UP1 - Université Paris 1 Panthéon-Sorbonne - UP8 - Université Paris 8 Vincennes-Saint-Denis - UPN - Université Paris Nanterre - UEVE - Université d'Évry-Val-d'Essonne - CNRS - Centre National de la Recherche Scientifique - ENS Paris Saclay - Ecole Normale Supérieure Paris-Saclay

Post-Print from HAL

Abstract: Recent advances in Artificial Intelligence (AI) have increased the ability of organizations to analyze data to support decisions. However, there is little focus to date, on the potential role of AI in organizational knowledge creation. This paper develops a framework of organizational artificial knowledge creation based on a synthesis of the literature, and the implementation of a multi-agent AI in an organization. We identify five stages for developing organizational artificial knowledge: 1) Extracting and Collecting, 2) Curating, 3) Ingesting, 4) Training and Testing, 5) Analyzing and Predicting. We also identified two main practices triggered by the development of the AI multi-agent that distinguish them from traditional IS: the ability to initiate a dialogue between the different actors which can lead to the consolidation and aggregation of the organizational knowledge, and the ability to establish recursive and reflexive relation between individual knowledge and the organizational artificial knowledge.

Date: 2017-12-10
Note: View the original document on HAL open archive server: https://hal.parisnanterre.fr/hal-03110617
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Published in ICIS 2017, Dec 2017, Seoul, South Korea

Downloads: (external link)
https://hal.parisnanterre.fr/hal-03110617/document (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03110617

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().