Understanding Moroccan engineers' intentions to adopt AI for Job Application: An Empirical Analysis

Abstract

Despite the ongoing digitalization of the talent acquisition (TA) practices, there is a significant dearth of research pertaining with the use of AI for TA, leaving a significant gap of understanding of these initial stages of technology adoption. Specifically, end-user perception and readiness to accept the use of this technology.

This study aims to investigate candidates’ behavioral intention toward AI for job Application as a component of AI for TA. For this purpose, the constructs of our designed research model are grounded in both UTAUT and the Confidentiality, Integrity and Availability (CIA) framework. A structured questionnaire was used among 183 Moroccan engineers across several disciplines, to assess the impact of performance expectancy, effort expectancy, hedonic motivation, perceived confidentiality, and perceived availability on candidates' behavioral intention to use AI-based job applications. The primary data were analyzed by means of the PLS-SEM method. The findings revealed a significant and positive impact of the constructs in our model on behavioral intention, except for effort expectancy, which did not exhibit a direct influence on our dependent variable. Therefore, the assumed negative impact of Perceived Confidentiality has not been verified. The study suggests that Moroccan candidates are open to using AI for job applications, which could encourage organizations to integrate AI solutions into their talent acquisition processes. The finding can give insight to AI developers to enhance their tools to meet candidate expectations, empowering marketers to promote their innovations effectively.

Keywords: UTAUT, CIA framework, Artificial Intelligence, Talent acquisition, Recruitment, HRM.

JEL Classification : D83 ; M15 ; O33.

Paper type: Empirical research