Exploring trust in generative AI for higher education institutions: a systematic literature review focused on educators

Although Generative Artificial Intelligence (GenAI) offers transformative opportunities for higher education, its adoption by educators remains limited, primarily due to trust concerns. This systematic literature review aims to synthesise peer-reviewed research conducted between 2019 and August 2024 on the factors influencing educators’ trust in GenAI within higher education institutions. Using PRISMA 2020 guidelines, this study identified 37 articles at the intersection of trust factors, technology adoption, and GenAI impact in higher education from educators’ perspectives. Our analysis reveals that existing AI trust frameworks fail to capture the pedagogical and institutional dimensions specific to higher education contexts. We propose a new conceptual model focused on three dimensions affecting educators’ trust: (1) individual factors (demographics, pedagogical beliefs, sense of control, and emotional experience), (2) institutional strategies (leadership support, policies, and training support), and (3) the socio-ethical context of their interaction. Our findings reveal a significant gap in institutional leadership support, whereas professional development and training were the most frequently mentioned strategies. Pedagogical and socio-ethical considerations remain largely underexplored. The practical implications of this study emphasise the need for institutions to strengthen leadership engagement, align GenAI adoption strategies with educators’ values, and develop comprehensive training frameworks that address ethical and pedagogical concerns. This work contributes a multidimensional view of educators’ trust in GenAI and provides a foundation for future research.

Authors

Institutions

Publication Details

Journal
Humanities and Social Sciences Communications
Published
2025-11-24
DOI
https://doi.org/10.1057/s41599-025-06253-1
Citations
3
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
1.96
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring trust in generative AI for higher education institutions: a systematic literature review focused on educators

Gabriela Grosseck, Laura Maliţa, Simona Sava, Ana Lelescu
3 citations
Humanities and Social Sciences Communications
Artificial Intelligence in Healthcare and Education
1.96
article

Exploring trust in generative AI for higher education institutions: a systematic literature review focused on educators

Gabriela Grosseck, Laura Maliţa, Simona Sava, Ana Lelescu
article en
3 citations

Abstract

Although Generative Artificial Intelligence (GenAI) offers transformative opportunities for higher education, its adoption by educators remains limited, primarily due to trust concerns. This systematic literature review aims to synthesise peer-reviewed research conducted between 2019 and August 2024 on the factors influencing educators’ trust in GenAI within higher education institutions. Using PRISMA 2020 guidelines, this study identified 37 articles at the intersection of trust factors, technology adoption, and GenAI impact in higher education from educators’ perspectives. Our analysis reveals that existing AI trust frameworks fail to capture the pedagogical and institutional dimensions specific to higher education contexts. We propose a new conceptual model focused on three dimensions affecting educators’ trust: (1) individual factors (demographics, pedagogical beliefs, sense of control, and emotional experience), (2) institutional strategies (leadership support, policies, and training support), and (3) the socio-ethical context of their interaction. Our findings reveal a significant gap in institutional leadership support, whereas professional development and training were the most frequently mentioned strategies. Pedagogical and socio-ethical considerations remain largely underexplored. The practical implications of this study emphasise the need for institutions to strengthen leadership engagement, align GenAI adoption strategies with educators’ values, and develop comprehensive training frameworks that address ethical and pedagogical concerns. This work contributes a multidimensional view of educators’ trust in GenAI and provides a foundation for future research.

Humanities and Social Sciences CommunicationsVol. 12(1)
West University of Timişoara (RO)
Openalex Percentile: Top 10%
Artificial Intelligence in Healthcare and Education
1.96
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Exploring trust in generative AI for higher education institutions: a systematic literature review focused on educators — Gabriela Grosseck, Laura Maliţa, et al. · Humanities and Social Sciences Communications (2025) | TGRS Research Map | TGRS