Artificial Intelligence in the Human Resources Domain: A Comprehensive Examination of Technologies, Applications, and Implications for the Future of Work

Authors

  • Hafiz Abdullah Department of Computer Science, Universiti Tenaga Nasional
  • Rafidah Binti Musa Department of Computer Science, Universiti Tun Hussein Onn Malaysia

Keywords:

Artificial Intelligence, Human Resources, Future of Work, Talent Management, HR Technologies

Abstract

Artificial Intelligence (AI) has emerged as a transformative force in the Human Resources (HR) domain, fundamentally changing how organizations manage human capital. From talent acquisition to employee engagement, performance management, and learning & development, AI is being utilized to improve efficiency, reduce biases, and enhance decision-making in HR processes. This research provides a comprehensive examination of the various AI technologies currently being employed in HR, analyzing their applications and implications for the future of work. Through an exploration of AI's impact on HR functionalities, this paper aims to contribute to the understanding of how AI can be leveraged to create value for both organizations and employees. The findings suggest that while AI offers numerous opportunities, it also presents ethical challenges and requires careful consideration of human-AI collaboration. The paper concludes with a discussion of future research directions and best practices for the integration of AI in HR to achieve positive organizational outcomes.

Author Biographies

Hafiz Abdullah, Department of Computer Science, Universiti Tenaga Nasional

 

 

 

Rafidah Binti Musa, Department of Computer Science, Universiti Tun Hussein Onn Malaysia

 

 

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Published

2020-12-08

How to Cite

Hafiz Abdullah, & Rafidah Binti Musa. (2020). Artificial Intelligence in the Human Resources Domain: A Comprehensive Examination of Technologies, Applications, and Implications for the Future of Work. Sage Science Review of Educational Technology, 3(1), 87–97. Retrieved from https://journals.sagescience.org/index.php/ssret/article/view/195