Nexus of Human‐AI Trust Equation: Competence, Ethics, and Self‐Efficacy as Drivers of Career Growth and AI‐Supported Decision Involvement

Abstract

Generative artificial intelligence is increasingly being incorporated into education and career development, raising important questions about how trust influences user participants, ethical awareness, and career‐related behavior. However, how trust translates into effective AI use under different psychological mechanisms and contextual conditions remains insufficiently understood. This study aims to examine how trust in generative AI influences career advancement behaviors and participation in AI‐integrated decision making, as well as the mediating roles of digital self‐efficacy and AI ethical awareness, and the moderating role of AI training exposure. Data were collected from 365 international students over three months using validated survey instruments measuring trust in AI, digital self‐efficacy, ethical awareness, and behavioral outcomes. Purposive sampling strategy targeted students engaged with AI based learning, and the data were analyzed using SmartPLS‐based Structural Equation Modeling (SEM). The results show that trust in generative AI has significant direct effects on career advancement behaviors and participation in AI‐integrated decision‐making. Digital self‐efficacy and AI ethical awareness both serve as significant mediators in these relationships. In addition, AI training exposure significantly moderates the effects of trust on digital self‐efficacy and ethical awareness. This study demonstrated that trust in generative AI exerts a pivotal influence through digital self‐efficacy and AI ethical awareness, thereby promoting individuals’ career advancement behaviors and participation in AI‐integrated decision‐making. The findings further indicate that the sustainable and responsible use of generative AI depends on the synergistic effects of trust, self‐efficacy, and ethical awareness within supportive training environments.