The impacts of AI and automation on human resource management – systematic review
DOI:
https://doi.org/10.34117/bjdv11n2-079Keywords:
artificial intelligence, automation, human resource management, recruitment and selection, vocational training, ethical challenges, data protection, bias in algorithms, human intervention, professional requalificationAbstract
This study focuses on the growing impact of Artificial Intelligence (AI) and automation on the Human Resource Management (HRM) processes of organizations. It examines how these emerging technologies are redefining HRM practices, with a particular focus on recruitment, training and human capital management. A methodology was used that integrates a quantitative analysis, derived from data collected through a structured survey on a Likert scale, and a systematic review of the literature. This two-pronged approach allowed us to assess perceptions about the implementation of AI in HRM and to identify emerging trends and patterns in recent studies. The results show that AI and automation contribute to greater efficiency in recruitment and selection processes, promoting greater equality in the identification and progression of talent. There was also a positive impact on skills development and vocational training, underlining the importance of adaptive strategies for the continuous development of employees. We face ethical and privacy challenges regarding the use of AI in HR. It highlights the need for robust practices for the protection of employee data and the prevention of bias and discrimination in algorithms. The importance of human intervention in automated decisions is highlighted, ensuring the maintenance of fairness and ethics, as well as the need for professional requalification in the face of technological changes. The study concludes that despite the challenges, AI and automation offer unprecedented opportunities for innovation in HRM. Organizations that integrate these technologies with the human elements of work are better prepared for a dynamic and technologically advanced future.
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