Transforming Educational HR Management: Integrating AI and Data Analytics for Enhanced Teacher Performance and Student Outcomes

The increasing adoption of digital technologies in education has reshaped how human resource (HR) management functions are conducted in academic settings. This study examines the transformative potential of artificial intelligence (AI) and data analytics in educational HR management, focusing on their impact on teacher performance and student outcomes. As educational institutions adopt technology-driven solutions, AI tools present new opportunities for optimizing HR functions such as recruitment, performance evaluation, and professional development. Using a mixed-methods approach combining quantitative surveys and qualitative interviews with educators and HR professionals, this research evaluates the effectiveness of AI-driven HR practices. The findings show that AI tools enhance teacher performance by offering personalized feedback, streamlining administrative tasks, and improving professional development. Quantitative results reveal a positive correlation between AI use in HR management and increased teacher effectiveness, leading to better student engagement and academic achievement. Qualitative insights indicate that HR managers value AI for enhancing efficiency and reducing bias, while teachers appreciate actionable feedback. Despite these benefits, ethical concerns arise around data privacy, teacher autonomy, and over-reliance on technology for performance evaluations. To address these challenges, the study recommends establishing ethical guidelines, investing in AI-related training, and conducting longitudinal studies to understand AI's long-term impacts. This research contributes to the growing literature on AI in education by demonstrating its potential to improve HR processes and educational outcomes. The findings offer valuable insights for educators, HR professionals, and policymakers aiming to leverage AI benefits while maintaining a human-centered approach in educatio