Navigating the AI Landscape in Talent Acquisition: Examining Managerial Awareness and Perceived Talent Management Impact

Abstract

This study investigates the awareness, adoption factors, and perceived impact of Artificial Intelligence (AI) within the talent acquisition (TA) process among Human Resource (HR) and Talent Acquisition managers. Amidst an evolving hiring landscape characterized by competition for skilled labor, AI has emerged as a transformative force in TA. This research employs a deductive and descriptive approach, utilizing a self-administered questionnaire distributed to 280 HR and TA professionals, complemented by a comprehensive literature review and semi-structured interviews. The quantitative data, collected from 116 valid responses, was analyzed using descriptive statistics, Chi-Square tests, and One-Way ANOVA to address three key research questions: the level of AI awareness, the factors influencing AI adoption and usage, and the perceived impact of AI on broader talent management practices. Descriptive analysis revealed a general awareness of AI tools among respondents. However, Chi-Square test results indicated no statistically significant relationship between AI training and actual AI usage in TA. Furthermore, the One-Way ANOVA demonstrated a statistically significant difference in perceived AI impact scores across varying frequencies of AI usage in different HR domains (Retention, Learning, Performance, and Potential). These findings provide empirical insights into the current state of AI integration in TA from the perspective of HR and TA managers, highlighting the nuances of awareness, adoption drivers, and perceived consequences for talent management.