From Automation to Ethics: Responsible AI in Human Resource Management across Industries with Insights from the Power Sector

The integration of Artificial Intelligence (AI) in Human Resource Management (HRM) is revolutionising workforce management by automating recruitment, performance evaluations, and employee engagement processes. However, AI-driven HRM systems raise critical ethical concerns, particularly regarding bias, privacy, and transparency. This study explores the ethical implications of AI adoption in HRM, with a specific focus on the power sector, where automation plays a crucial role in workforce optimisation. The research employs a quantitative approach, analysing responses from 250 employees across various departments in power sector organisations. Using SPSS, key statistical tests—including factor analysis, correlation, regression, and ANOVA—are applied to examine the relationships between AI bias, privacy concerns, transparency, employee trust, and job satisfaction. Findings reveal that AI bias significantly affects workforce diversity, while privacy concerns negatively impact employee trust in AI-driven HR decisions. Moreover, the study highlights that greater transparency in AI decision-making fosters higher employee satisfaction and engagement. The study underscores the need for organisations to implement ethical AI governance frameworks to ensure fair, unbiased, and privacy-compliant AI systems in HRM. It recommends explainable AI models, fairness audits, and hybrid decision-making (AI + human oversight) to enhance trust and acceptance of AI-driven HR practices. These findings contribute to the broader discourse on responsible AI adoption in HRM, offering strategic insights for HR leaders, policymakers, and AI developers in the power sector.