Navigating the Algorithmic Frontier: The Impact of AI-Based Recruitment Exposure and Fairness Perception on Generation Z’s Intent to Apply with Trust as a Mediator - Lisa Nur'Aini; Febrianty; Anita (Yayasan Multidimensi Kreatif, 2026)
This study aims to analyze the factors influencing Generation Z's intention to apply for jobs through Artificial Intelligence (AI)-based recruitment platforms. Utilizing the Technology Acceptance Model (TAM) as a theoretical framework, this research examines the impact of AI-based recruitment exposure and algorithmic fairness perception on the intention to apply, with trust in the system as a mediating variable. Data were collected via online questionnaires from 110 Generation Z respondents in Bandar Lampung City who are active users of digital job portal platforms. Data analysis was performed using Partial Least Squares Structural Equation Modeling (PLS-SEM) assisted by SmartPLS software. The results indicate that AI-based recruitment exposure and algorithmic fairness perception have a positive and significant influence on Generation Z's intention to apply. Furthermore, both independent variables were found to enhance candidate trust in automated recruitment systems. The mediation analysis confirms that trust plays a crucial role as a mediator linking technological experience and fairness perceptions with the actual behavioral intention to apply for a job. These findings provide practical implications for companies and HR practitioners to prioritize algorithmic transparency and data security to build the trust of young talent in the era of digital transformation.