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All Journal International Journal of Multidisciplinary Research of Higher Education (IJMURHICA)
Kamil, Camelia
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Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media Social Sciences

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The Mediating Role of Trust in Generation Z’s Intention to Use AI-Based Career Preparation Systems Kamil, Camelia; Roostika, Ratna
International Journal of Multidisciplinary Research of Higher Education Vol 9 No 2 (2026): (April) Theme Education, Religion Studies, Social Sciences, STEM and Economic Dev
Publisher : Islamic Studies and Development Center in Collaboration With Students' Research Center Universitas Negeri Padang

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Abstract

This study investigates the adoption behavior of Generation Z in using artificial intelligence as a career preparation assistant by extending the Unified Theory of Acceptance and Use of Technology (UTAUT) with Information Quality and Trust. The research examines how information quality shapes performance expectancy and trust, and how performance expectancy, effort expectancy, social influence, facilitating conditions, and trust influence the intention to continue using AI-based career tools. A quantitative explanatory design with exploratory elements was employed. Data were collected via an online questionnaire distributed to Generation Z individuals who have used AI for career-related activities, yielding 213 valid respondents. The data were analyzed using PLS-SEM. The findings reveal that information quality significantly enhances both performance expectancy and trust. Performance expectancy, social influence, and facilitating conditions had significant positive effects on the intention to continue using AI for career preparation. Trust also demonstrated a crucial mediating role in reinforcing continued usage intention. Meanwhile, effort expectancy did not significantly affect intention to continue. Overall, the results highlight the importance of delivering accurate, relevant, and reliable AI-generated information and building user trust to support sustained AI adoption among Generation Z. These insights provide practical guidance for developers, educators, and career service providers in optimizing AI systems to strengthen long-term engagement.
Co-Authors Ratna Roostika