AI-Powered HRM and Finance Information Systems for Workforce Optimization and Employee Engagement

  • Devaraju S
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Abstract

This comprehensive analysis examines the implementation and impact of AI-powered Human Resource Management (HRM) and Finance Information Systems in government organizations, focusing on workforce optimization and employee engagement. The study, drawing from extensive research across multiple public sector entities, reveals that organizations implementing these systems achieve significant improvements in operational efficiency, with processing times reduced by 47.2% and budgetary allocation accuracy increased by 31.4%. Through analysis of implementation data from 156 federal agencies, the research demonstrates how AI-driven solutions address key challenges in regulatory compliance, budget constraints, and operational transparency. The investigation encompasses four core functional areas: intelligent recruitment, workforce planning, employee experience enhancement, and financial management integration, supported by machine learning algorithms and cloud infrastructure. The results show significant progress in every area, including a noteworthy 56.8% decrease in hiring bias, a 41.3% increase in staff retention, and an 82.6% accuracy rate in document classification.

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Devaraju, S. (2024). AI-Powered HRM and Finance Information Systems for Workforce Optimization and Employee Engagement. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 15(1), 269–281. https://doi.org/10.61841/turcomat.v15i1.14940

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