DEVELOPMENT OF ARTIFICIAL INTELLIGENCE TECHNOLOGY ACCEPTANCE MODEL IN THE RECRUITMENT AND SELECTION PROCESS BY RECRUITERS

Abstract

This study develops a technology acceptance model for artificial intelligence (AI) in the recruitment and selection process conducted by recruiters. A quantitative approach was employed, collecting data from 90 recruiters in the Greater Jakarta and Bandung areas through a questionnaire comprising 25 indicators across seven research variables. The data were analyzed using the PLS-SEM method with the help of SmartPLS software. The model adapts the Unified Theory of Acceptance and Use of Technology (UTAUT), incorporating variables such as performance expectancy, effort expectancy, social influence, and facilitating conditions. Additionally, trust and attitude were included as independent and mediating variables to strengthen the model. The findings indicate that performance expectancy and trust significantly influence recruiters' attitudes, while attitude and social influence directly impact recruiters' intention to use AI. This research provides empirical and conceptual contributions to understanding AI technology acceptance in human resource management, particularly in the recruitment and selection process.