Evaluation of the use of artificial intelligence in recruitment processes in private education

Abstract

The digital transformation of private educational institutions has placed considerable emphasis on the need to modernize human talent management processes through artificial intelligence (AI), raising questions about the current implementation and operational functionality of the phenomenon under study. Therefore, this research aims to comprehensively evaluate the use of artificial intelligence in personnel selection in private educational institutions through the analysis criteria of implementation, operational functionality, and organizational determinants. The study employed a quantitative, non-experimental, cross-sectional, and descriptive method design. Consequently, the population consists of 51 professionals working in human talent management, and the sample was selected using a non-probabilistic convenience sampling method. Two validated questionnaires were developed: “Artificial Intelligence” (α = 0.969, consisting of five dimensions) and “Personnel Selection” (α = 0.976, consisting of three dimensions), analyzed using descriptive statistical analysis techniques and joint distribution tables, respectively. The results reveal critical differences in conceptual mastery, with only 17.6% of respondents demonstrating efficient mastery of AI and 47.1% demonstrating substantial deficiencies, and significant limitations in selection functionality, with 51% of participants considering selection to be “poor”.  Likewise, the analysis of organizational patterns resulted in three distinct profiles, proving the systematic interdependence between technology and operational functionality. Consequently, private educational institutions are clearly at an early stage of technology implementation, as there are critical gaps between theoretical potential and current readiness and, as a result, they need a holistic change approach that takes into account the specificities of the contemporary educational niche.