AI governance on young consumers in higher education: a content analysis of policies for generative AI

Purpose As generative artificial intelligence (AI) technologies continue to advance and become more prevalent in higher education, addressing the ethical concerns associated with their use is essential. This study emphasizes the need for robust AI governance as more young consumers increasingly use generative AI for various applications. This paper aims to examine the ethical challenges posed by generative AI and review the AI policies in higher education to regulate young consumers use of generative AI, focusing on the ethical use of AI from foundational principles to sustainable governance. Design/methodology/approach Through a content analysis of literature on generative AI policies in higher education published between 2020 and 2024, this research aims to explore a more holistic approach to integrating generative AI into the educational process. The analysis examines academic policies and governance framework from 28 journal papers regarding generative AI tools in higher education. Data were collected from publicly accessible sources, such as Scopus, Emerald Insights, ProQuest, Web of Science and ScienceDirect. Findings This study analyses ten elements of the governance framework to identify potential AI governance and policy setting, benefiting stakeholders aiming at enhancing the regulatory framework of generative AI use in higher education. The discussions indicate a generally balanced yet cautious approach to integrating generative AI technology, especially considering ethical issues, inherent limitations and data privacy concerns. Originality/value The findings contribute to ongoing discussions to strengthen universities’ responses to new academic challenges posed by the use of generative AI and promote high AI ethical standards across educational sectors.

Authors

Institutions

Publication Details

Journal
Young Consumers Insight and Ideas for Responsible Marketers
Published
2025-08-25
DOI
https://doi.org/10.1108/yc-10-2024-2303
Citations
2
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
1.31
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI governance on young consumers in higher education: a content analysis of policies for generative AI

Zahirah Zainol, A. K. W. TONG, Teck Siong Chong, Krishnamoorthy Renganathan
2 citations
Young Consumers Insight and Ideas for Responsible Marketers
Artificial Intelligence in Healthcare and Education
1.31
article

AI governance on young consumers in higher education: a content analysis of policies for generative AI

Zahirah Zainol, A. K. W. TONG, Teck Siong Chong, Krishnamoorthy Renganathan
article en
2 citations

Abstract

Purpose As generative artificial intelligence (AI) technologies continue to advance and become more prevalent in higher education, addressing the ethical concerns associated with their use is essential. This study emphasizes the need for robust AI governance as more young consumers increasingly use generative AI for various applications. This paper aims to examine the ethical challenges posed by generative AI and review the AI policies in higher education to regulate young consumers use of generative AI, focusing on the ethical use of AI from foundational principles to sustainable governance. Design/methodology/approach Through a content analysis of literature on generative AI policies in higher education published between 2020 and 2024, this research aims to explore a more holistic approach to integrating generative AI into the educational process. The analysis examines academic policies and governance framework from 28 journal papers regarding generative AI tools in higher education. Data were collected from publicly accessible sources, such as Scopus, Emerald Insights, ProQuest, Web of Science and ScienceDirect. Findings This study analyses ten elements of the governance framework to identify potential AI governance and policy setting, benefiting stakeholders aiming at enhancing the regulatory framework of generative AI use in higher education. The discussions indicate a generally balanced yet cautious approach to integrating generative AI technology, especially considering ethical issues, inherent limitations and data privacy concerns. Originality/value The findings contribute to ongoing discussions to strengthen universities’ responses to new academic challenges posed by the use of generative AI and promote high AI ethical standards across educational sectors.

Young Consumers Insight and Ideas for Responsible MarketersVol. 26(5)
Curtin University (AU), University of Newcastle Australia (AU)
Openalex Percentile: Top 14%
Artificial Intelligence in Healthcare and Education
1.31
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.