Understanding Candidates' Behavioral Intentions toward AI for Talent Acquisition: A Conceptual Study Using UTAUT and CIA Frameworks

Résumé

Abstract

The objective of this conceptual study is to propose an enhanced model of factors that impact candidates' behavioral intention (BI) to accept the use of AI solutions for TA, including factors related to the privacy and security of this new technology. By integrating the Unified Theory of Technology Acceptance and Use (UTAUT) and the Confidentiality, Integrity and Availability (CIA) framework, the proposed model examines the impact of performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), hedonic motivations (HM) and habit (HAB), perceived confidentiality (PC), perceived integrity (PI) and perceived availability (PA) on candidates' BI towards AI for TA. The proposed model contributes to existing knowledge by integrating security and privacy as a new perspective to the original model that can impact candidate behavior towards AI in TA.

Keywords: Artificial Intelligence, Talent Acquisition, UTAUT, CIA Framework, Candidate Behavior, Behavioral Intention