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Impact of Artificial Intelligence on Human Resource Decision-Making: The Mediating Roles of Ethical AI Practices and Human Oversight in Nepalese Organizations

Sep 2026 · KVM Research Journal · 0 citations · 28 references

TL;DR

Overall, the study demonstrates that AI can be optimized in HR decision-making processes through ethical governance AI practices and human review, which includes the mediating role of ethical AI practices and the moderating role of human monitoring of AI-driven automated HR processes.

Abstract

The increasing use of artificial intelligence (AI) is currently transforming HRM by challenging the very nature of HR decision making. The study explores the effect of artificial intelligence on human resource decision making in Nepalese organizations with a specific focus on ethical AI and human oversight. The quantitative research method was used to gather data from 260 respondents (HR professionals, line managers, and employees) who represent different sectors in Nepal through the developed structured questionnaires. Descriptive, reliability,Pearson’s product-moment moment correlation, multiple regression analyses, and bootstrapped mediation were performed to analyze the data. The results of the study revealed that adopting AI in human resource management, using AI-based analytics and automating HR processes will improve decision-making quality. Additionally, the indirect influence of general AI adoption, AI analytics, and decision-making effectiveness was partially mediated by ethical AI practices and moderated by human oversight of automated HR processes. On the contrary, there was no significant interaction between general AI adoption and human overseer-ship on decision‐making effectiveness. Overall, the study demonstrates that AI can be optimized in HR decision-making processes through ethical governance AI practices and human review. This includes the mediating role of ethical AI practices and the moderating role of human monitoring of AI-driven automated HR processes. This study contributes to the AI–HRM literature by providing empirical evidence from a developing economy context and some practical implications for responsible and human-enhanced AI decision making in organizations.

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