Analyzing Trends, Gaps, And Future Directions in Human Resources Management Through Artificial Intelligence and Machine Learning
The role of Artificial Intelligence and Machine Learning transformation in the field of Human Resource Management is in the spotlight for research, especially in the recruitment process. This research conducted a literature review and bibliometric analysis of 363 Scopus indexed articles published in 2020 until 2025. Through this research, there are three parts that will be explored further, namely identifying current trends, research gaps and future research directions. The findings reveal that artificial intelligence and machine learning significantly improve the recruitment process, making it less time-consuming and more accurate in candidate selection. Challenges faced in implementing the use of artificial intelligence and machine learning still exist such as the challenges of algorithmic model bias, data privacy and others. This research also looks at critical gaps such as the future impact of artificial intelligence on employee satisfaction, performance, retention, as well as the integration of human collaboration that requires time to implement or expertise. This analysis highlights the significance of responsible execution of AI, with proposals for longitudinal considerations, and cross breed models including both machine choice making and human judgment. Filling these voids will way better permit artificial intelligence and machine learning to help make HR more beneficial, reasonable and sustainable.
Authors:
Farah Fitriavida Arifin, Andrea Stevens Karnyoto, Bens Pardamean
2025 International Conference on Informatics and Computing (ICIC)