From Human Judgment to Algorithmic Insight: Artificial Intelligence in Talent Identification, Retentionand Succession Planning

Abstract

The rapid adoption of artificial intelligence (AI) in human resource management has transformed traditional approaches to talent identification, employee retention, and succession planning. This study investigated the role of AI in enhancing organisational talent management processes using a quantitative research design. Data were collected from human resource professionals and managers across medium-and large-sized organisations via a structured online questionnaire. Descriptive statistics, correlation analysis, and multiple regression techniques were employed to analyse the data. The findings indicated that AI adoption significantly improved talent identification by enabling data-driven decisions, enhancing accuracy, and facilitating the recognition of high-potential employees. Talent identification, in turn, positively influenced employee retention, suggesting that AI-supported recruitment and assessment strategies fostered workforce stability and reduced turnover intentions. Furthermore, employee retention had a substantial impact on succession planning, supporting the development of leadership pipelines and ensuring organisational continuity. The results underscore the sequentialand interconnected effects of AI-enabled HR practices, highlighting a shift from subjective human judgment to predictive, evidence-based decision-making. Ethical considerations, human oversight, and competency development were identified as critical factors for the effective implementation of AI in HR processes. The study provides practical insights for organisations seeking to leverage AI for strategic talent management while maintaining fairness, transparency, and employee trust.