Publication Details
Abstract
Objective: The purpose of this study is to present a predecessor–successor model explaining the impact of artificial intelligence on human resource development (HRD). Method: The present research is applied in nature and conducted through a qualitative research approach using content analysis. The data collection method was qualitative and carried out through a library-based study, involving the review of books, articles, and theses. Results: The findings indicated that the antecedents influencing the impact of AI on HRD can be classified into several categories. The first group includes technical and data-related factors, such as technological infrastructure and integration, informational and communication factors, information quality, data mining, intelligence requirements, and functional requirements. The second group involves human and organizational factors; the third group includes managerial and process factors; the fourth group covers environmental and industrial factors; and finally, the fifth group comprises legal, ethical, and perceived benefit factors. Additionally, the consequences (successors) of AI implementation in HRD can also be categorized into several main groups: the first group relates to improved performance and productivity; the second group to employee development and advancement; the third group to motivation, satisfaction, and employee experience; the fourth group to innovation and knowledge management; and the fifth group to organizational relationships and structures. Novelty: The study introduces a predecessor–successor model that categorizes the antecedents and consequences of AI’s impact on human resource development, distinguishing technical, organizational, managerial, environmental, and ethical factors, and their influence on HRD outcomes such as performance, employee satisfaction, innovation, and organizational structure.