Reference Hub6
Unrealistic Optimism Regarding Artificial Intelligence Opportunities in Human Resource Management

Unrealistic Optimism Regarding Artificial Intelligence Opportunities in Human Resource Management

Patrick Weber
Copyright: © 2023 |Volume: 19 |Issue: 1 |Pages: 19
ISSN: 1548-0666|EISSN: 1548-0658|EISBN13: 9781668479001|DOI: 10.4018/IJKM.317217
Cite Article Cite Article

MLA

Weber, Patrick. "Unrealistic Optimism Regarding Artificial Intelligence Opportunities in Human Resource Management." IJKM vol.19, no.1 2023: pp.1-19. http://doi.org/10.4018/IJKM.317217

APA

Weber, P. (2023). Unrealistic Optimism Regarding Artificial Intelligence Opportunities in Human Resource Management. International Journal of Knowledge Management (IJKM), 19(1), 1-19. http://doi.org/10.4018/IJKM.317217

Chicago

Weber, Patrick. "Unrealistic Optimism Regarding Artificial Intelligence Opportunities in Human Resource Management," International Journal of Knowledge Management (IJKM) 19, no.1: 1-19. http://doi.org/10.4018/IJKM.317217

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

Artificial intelligence (AI) has many uses in domains like automotive and finance or business divisions like human resource management (HRM). This study presents a survey that was conducted among a German national sample (n = 79) of HRM personnel from small- and medium-sized enterprises regarding the expected impact of AI on their own and other companies. Indications for unrealistic optimism, i.e., assuming negative impacts are more likely for others than oneself, were identified. AI will play an increasingly important role, with cost reductions and efficiency gains serving as the highest motives and a lack of AI specialists representing the highest inhibitor. Participants assume that AI will reduce the number of employees in other companies, while it let the one in their own grow. They expect AI to take over more tasks in other companies and believe AI will more impact other companies' HRM, especially in administrative processing. Future research should include (repeated) investigations into other business divisions.