A comprehensive analysis of the implications of artificial intelligence adoption on employee social well-being in South African facility management organizations

• Published in: Journal of corporate real estate Vol. 26; no. 3; pp. 237 - 261
• Main Authors: Moghayedi, Alireza, Michell, Kathy, Awuzie, Bankole, Adama, Unekwu Jonathan
• Format: Journal Article
• Language: English
• Published: Bingley Emerald Publishing Limited 19-07-2024; Emerald Group Publishing Limited
• Subjects: Artificial intelligence; Employees; Innovations; Productivity; Technology adoption; South Africa; South Africa; Artificial intelligence; Employee
• ISSN: 1463-001X; 1463-001X; 1479-1048
• DOI: 10.1108/JCRE-09-2023-0041

Purpose
The purpose of this study is to explore the increased uptake of Artificial Intelligence (AI) technology by Facility Management (FM) organizations for enhanced operational efficiency and competitive advantage. While AI adoption in FM has been widely reported, limited attempts have been made to assess its impact on the social well-being of FM employees. To contribute towards addressing this gap, this study established the essential employee social well-being factors mostly impacted by the adoption of AI in South African FM organizations.
Design/methodology/approach
A four-stage design comprising a comprehensive review of literature, expert interviews, questionnaire census and focus group discussion sessions was used to elicit data from a sample of participants drawn from 22 South African FM organizations. The data was analyzed using a combination of content analysis, relative importance index and interpretative structural modeling for various data sets toward achieving the study’s objectives.
Findings
Sixteen employee social well-being factors, classified under job satisfaction, social relationship and knowledge development categories, respectively, were identified as being impacted by AI adoption in FM organizations. Furthermore, it was established that job security, job autonomy and professional status, which belong to the job satisfaction social well-being factor category, were deemed by FM employees as being mostly impacted by AI adoption.
Practical implications
The enhanced understanding of the impact of AI adoption on FM employees’ social well-being factors will contribute to the development of a collaborative intelligence framework for managing AI adoption in FM organizations toward engendering optimal AI–FM employee relationships for improved productivity.
Originality/value
Besides being one of the foremost studies to investigate the impact of AI adoption on FM employees’ social well-being, this study introduces a hierarchical framework of understanding employee social well-being factors based on multi-stakeholder perspectives.