AI-Powered HRM and Finance Information Systems for Workforce Optimization and Employee Engagement
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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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References
Mingxin Fan, " Research on Digital Transformation of Human Resource Management in Public Sector," ICPDI 2023, September 01-03, Chongqing, People's Republic of China, 2023. [Online]. Available: https://eudl.eu/pdf/10.4108/eai.1-9-2023.2338722
Michael J. Keegan, " More Than Meets AI: Assessing the Impact of Artificial Intelligence onthe Work of Government," IBM Center for The Business of Government, 2023. [Online]. Available:https://www.businessofgovernment.org/sites/default/files/More% 20Than%20Meets%20AIAssessing%20the%20Impact%20of%20Artificial%20Intelligence%20on%20the%20Work%20of%20Government.pdf
Swati Garg, Shuchi Sinha, Arpan Kumar Kar, Mauricio Mani, " A review of machine learning applications in human resource management," International Journal of Productivity andPerformance Management, Feb. 2021. [Online]. Available:
https://www.emerald.com/insight/content/doi/10.1108/IJPPM-08-2020-0427/full/html
Dipanker Sharma, Waleed Salehi, Bhawana Bhardwaj, Mohinder Chand, and Hasiba Salihy, "Dovetailing human resource management with cloud computing in the era of industry 4.0: A review," Frontiers in Management and Business, vol. 4, no. 2, pp. 78-95, 2023. [Online].
Available: https://www.syncsci.com/journal/FMB/article/view/FMB.2023.02.004
Anna Brown, Daniel Smith, "Artificial Intelligence in HR Recruitment: Enhancing Efficiency," Journal of HR Tech Advances, vol. 6, no. 2, 2022. [Online]. Available: https://hrtechadvances.com/article/ai-recruitment-enhancing-efficiency-2022
Ethan Taylor, Priya Chopra, "AI-Powered Analytics in Workforce Management," AI Workforce Management Review, vol. 9, no. 3, 2023. [Online]. Available:https://aianalyticsjournal.com/ai-powered-workforce-analytics-2023
Sobia Wassan, et. al., " How Artificial Intelligence Transforms the Experience of Employees,"TURCOMAT, 2021. [Online]. Available: https://www.turcomat.org/index.php/turkbilmat/article/view/5603
Sanket L. Charkha and Sunita Nikhil Shah, " Financial Management and Human Resource Management Correlations & Interdependence between these two Disciplines and its Activities" 1st International Conference on Leadership—September 15, 2023. [Online]. Available:https://www.researchgate.net/publication/375698035_Financial_Management_and_Human_Resource_Management_Correlations_Interdependence_between_these_two_Disciplines_and_it
s_Activities_Sunita_Nikhil_Shah
Alexis Megan Votto, Rohit Valecha, Peyman Najafirad, and H. Raghav Rao, " Artificial Intelligence in Tactical Human Resource Management: A Systematic Literature Review."International Journal of Information Management Data Insights, Volume 1, Issue 2, November 2021, 100047. [Online]. Available:
https://www.sciencedirect.com/science/article/pii/S2667096821000409
Samiya Alhinaai, " Change Management in Digital Transformation," International Conference on the Leadership and Management of Projects in the Digital Age (IC: LAMP 2022) at: Kingdom of Bahrain, June 2023. [Online]. Available:
https://www.researchgate.net/publication/371304223_Change_Management_in_Digital_Transformation
Alouis Chilunjika, Kudakwashe Intauno, Sharon R. Chilunjika, " Artificial intelligence and public sector human resource management in South Africa: Opportunities, challenges and prospects," SA Journal of Human Resource Management, vol. 20, a1972, 2022. [Online].
Available: https://sajhrm.co.za/index.php/SAJHRM/article/view/1972
K Rangana Samarasinghe and Dr. Ajith Medis, "Artificial Intelligence-Based Strategic Human Resource Management (AISHRM) For Industry 4.0," Global Journal of Management and Business Research: G Interdisciplinary, Vol. 20 No. G2 (2020): GJMBR-G Interdisciplinary: Volume 20 Issue G2. [Online]. Available:
https://journalofbusiness.org/index.php/GJMBR/article/view/3059
Osea Giuntella, Johannes König, Luca Stella, "Artificial Intelligence and Workers’ Well-Being," IZA Discussion Paper No. 16485, 2023. [Online]. Available: https://docs.iza.org/dp16485.pdf
Anneke Zuiderwijk, Yu-Che Chen, Fadi Salem, " Implications of the use of artificial intelligence in public governance: A systematic literature review and a research agenda,"Government Information Quarterly, vol. 38, no. 3, 101577, 2021. [Online]. Available:https://www.sciencedirect.com/science/article/pii/S0740624X21000137
Tiago C. Peixoto and Jonathan Fox, "When Does ICT-Enabled Citizen Voice Lead to Government Responsiveness?" World Development, vol. 99, pp. 335–349, 2017. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0305750X17302308