Citation: Smuts, H.; Van der Merwe, A. Knowledge Management in Society 5.0: A Sustainability Perspective. Sustainability 2022, 14, 6878. https://doi.org/10.3390/ su14116878 Academic Editor: Víctor Jesús García-Morales Received: 8 May 2022 Accepted: 20 May 2022 Published: 4 June 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). sustainability Review Knowledge Management in Society 5.0: A Sustainability Perspective Hanlie Smuts 1,2, * and Alta Van der Merwe 1 1 Department of Informatics, University of Pretoria, Pretoria 0083, South Africa; alta.vdm@up.ac.za 2 Knowledge Management South Africa, 59 Woodlands Ave, Hurlingham Manor, Sandton 2196, South Africa * Correspondence: hanlie.smuts@up.ac.za Abstract: Organizations require the means to navigate Society 5.0. This is a knowledge-intensive society where a sustainable balance must be created for social good through a system that integrates cyberspace and physical space. With significant data, information and insight exchange based on knowledge in people and machines, organizations need to make sense of the notion that knowledge assets are the central structuring elements for sustainable development. By considering the key aspects of knowledge management (KM) in Society 5.0 as they relate to sustainable development, organizations may leverage their KM capability and learning agility to successfully address the unique requirements of the new society, environment and goals for sustainable development. In this research, automated content analysis was applied to identify key KM aspects using the Leximancer software. A total of 252 academic papers were analyzed, identifying 10 themes related to key KM concepts in Society 5.0 as they pertain to sustainability. The KM concepts identified were described and mapped to the sustainability triple bottom line. They comprised three primary and three intersecting dimensions, i.e., the environment (planet), society (people) and economic performance (profit) in the socio-economic, eco-efficiency and socio-environmental domains. The most significant themes included “knowledge”, “human”, “companies”, “information” and “system”. Secondary themes included “innovation”, “development”, “resources”, “social” and “change”. Keywords: knowledge management; sustainability; Society 5.0; triple bottom line; automated content analysis; research agenda 1. Introduction The world is experiencing radical advances in science and technology [1]. With the evolution of digital technologies comes a growing recognition that most workplaces are experiencing change [2,3]. Digital technologies, which are evolving at an exceptional rate, automate not only labor-intensive and repetitive work but also influence knowledge work [4,5]. This necessitates understanding and managing greater complexity [6,7]. Knowl- edge work relies, to a greater extent, on individuals’ cognitive abilities, as opposed to when work consists primarily of the execution of known procedures and manual actions [8,9]. Furthermore, knowledge is now recognized as being central to sustained organizational success [10–12]. Knowledge workers drive knowledge management (KM) processes [13]. The evolution of digital technologies has also changed the landscape and nature of KM [14,15]. The growing use of digital technologies has created completely new business models and means to create value [14,16]. Some of these include control and monitoring through computer-based algorithms, the on-demand availability of computing power and data storage, cognitive computing and the rise of a connected world [17,18]. Maintaining a KM emphasis in this context is important, as intelligent machines, such as those that use artificial intelligence (AI) and machine learning, are altering knowledge creation and sharing in organizations [16,19]. A key contributor to the viability of AI applications and the maturity of AI technologies is the availability of data that may be applied in computer learning processes [20,21]. In addition, structured and unstructured big data structures are Sustainability 2022, 14, 6878. https://doi.org/10.3390/su14116878 https://www.mdpi.com/journal/sustainability