Assessing the key drivers of acceptance of AI-based employee management across varied levels of employees working in the Australian IT industry

Xinyang Zhang () and Sanghyuk Yim ()

International Journal of Public Policy and Administration Research, 2025, vol. 12, issue 2, 151-167

Abstract: The purpose of this study is to assess key drivers of acceptance of AI-based employee management across various levels of employees working in the Australian IT industry. In the Australian IT industry, AI adoption in HRM, specifically in employee management, is increasing rapidly. Quantitative data collection and analysis have been conducted for this research. Data was collected from social media groups. Although the initial pool of candidates was 456, a total of 257 responses were received. After filtering out incomplete and invalid responses, 216 responses were considered for analysis. The results showed that the most significant driver of acceptance of AI-based employee management in the Australian IT industry, which ensures corporate social responsibility, is perceived transparency, fairness, and training and development sessions to enhance AI-related knowledge. There is no significant relationship between privacy and security and employee acceptance of AI integration into the employee management system. The positional level of employees in the Australian IT sector itself is a driver of higher AI acceptance. It has been suggested that managers prioritize CSR-driven initiatives, such as enhancing perceived transparency and fairness through the implementation of ethical AI practices. Additionally, both higher-level and lower-level employees should be involved in AI implementation processes to increase their acceptance levels.

Keywords: AI-based employee management; Artificial intelligence; Employee levels; Privacy and security; Training and development; Transparency and fairness. (search for similar items in EconPapers)
Date: 2025
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