Identifying Strategies for Enhancing Efficiency and Optimizing Human Resource Processes in Government Organizations Based on Artificial Intelligence
Keywords:
Efficiency, Optimization, Human Resource Management, Artificial IntelligenceAbstract
The present study aims to identify strategies for enhancing efficiency and optimizing human resource processes in government organizations based on artificial intelligence. The research method is library-field-based in terms of environment, applied in terms of purpose, cross-sectional in terms of data collection time, descriptive-survey in terms of research implementation method, and of a correlational and causal type. Additionally, considering the study's objectives and nature, a mixed-methods approach integrating qualitative and quantitative methods was employed. The statistical population in the qualitative section of the study consists of 30 experts and senior managers of government organizations in Tehran. In the quantitative section, the opinions of all employees of government offices in Tehran were utilized for statistical analysis. Cochran’s formula was used to determine the sample size for the quantitative section, resulting in a selection of 385 participants. For data analysis in the qualitative section, the fuzzy Delphi technique was employed. In the quantitative section, descriptive analyses utilized tests such as the one-sample t-test, while inferential analyses were conducted using SPSS software and the fuzzy Analytical Hierarchy Process (AHP) technique. The results indicated that strategies for enhancing efficiency and optimizing human resource processes in government organizations based on artificial intelligence include process automation, big data analysis, intelligent performance management systems, AI-based recruitment, and workforce needs prediction and analysis. Additionally, among these components, process automation ranked as the top priority, followed by workforce needs prediction and analysis in second place, AI-based recruitment in third place, big data analysis in fourth place, and intelligent performance management systems in fifth place.
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