AI in HRM: Unveiling Areas and Future Trajectories for Organizational Transformation

Human resource management is the backbone of business and organization. This study investigates AI's revolutionary effect on HRM by delving into AI's function in maximizing organizational and personnel development. This study analyses 1,505 articles from 1984 to 2024 using latent semantic analysis, which comes under the umbrella of natural language processing (NLP) techniques. The methodology relies on data extracted from Scopus. Preprocessing is made more accessible with the KNIME tool. In this study, the TF-IDF score is calculated, and based upon these scores, K-Mean clustering is applied to predict the recent areas on which future researchers can work. The report highlights the different applications of AI in HRM by identifying five unique clusters: HRM in the Education Sector, Data Learning and Technology, Workforce Management, Agriculture and Technology, Business and Project Management, and Data and Project Management. To help navigate the ever-changing junction of AI and human capital, the research ends by offering suggestions for future initiatives, such as ethical issues, long-term organizational impact, industry-specific adoption, and advanced natural language processing techniques.