To address the trust barriers hindering university teachers’ artificial intelligence (AI) literacy improvement, this study introduces a bidirectional human-AI trust perspective, extends the unified theory of acceptance and use of technology (UTAUT) model, and examines the formation mechanism and development pathways via partial least squares structural equation modeling (PLS-SEM) analysis of 1,519 valid questionnaires from Zhejiang Province. The findings indicate: (1) Teachers’ AI literacy presents a pattern of “solid basics but weak advanced competence”, with bidirectional trust imbalance as the core constraint. (2) All UTAUT core variables significantly affect AI literacy; bidirectional human-AI trust serves as a partial mediator, and AI’ s adaptive trust positively moderates the link between teachers’ trust in AI and literacy, forming a closed-loop effect. (3) There are notable heterogeneities across teaching experience, disciplines and institution types. This study further identifies three developmental stages and proposes a three-tiered targeted pathway, providing empirical support for advancing teachers’ AI literacy from basic use to sustainable, innovative application.
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Share and Cite
Zhu, S., Xu, S., Han, Z., You, Z. (2026) From Barriers to Breakthroughs: Formation Mechanism and Development Pathways of University Teachers’ AI Literacy Under Bidirectional Regulation of Human-AI Trust. Global Education Bulletin, 3(4), 21-30. https://doi.org/10.71052/grb2025/WLDI8972