Artificial intelligence in higher education: stakeholder perceptions and policy implications

Abstract

Purpose This study aims to examine stakeholder perceptions of artificial intelligence (AI) at a small regional comprehensive university in the southern United States to inform the development of ethical, transparent and inclusive institutional policies. Guided by an integrated conceptual framework, the study explored how stakeholder role and age influence perceptions of AI and identified perceived training and policy gaps related to responsible AI use. Design/methodology/approach Guided by the technology acceptance model, diffusion of innovations theory, the ethical decision-making framework and social constructivism, the study employed an exploratory survey design (n = 248) combining Likert-scale items and open-ended responses. Quantitative data were analyzed using descriptive and nonparametric statistics, and qualitative data were examined through thematic analysis to capture both patterns and contextual insights. Findings Results revealed significant differences in AI perceptions by role and age. Students were highly accepting of AI for learning and efficiency, whereas faculty and administrators expressed greater concern about academic integrity, privacy and ethical use. Staff responses were mixed, emphasizing workflow efficiency alongside ethical and governance-related risks. Across groups, participants highlighted the need for clearer guidelines and structured training to support responsible AI adoption. Research limitations/implications The single-institution, cross-sectional design may limit transferability. Future research could extend these findings through multi-institutional, longitudinal or qualitative studies that further examine evolving AI governance and practice. Practical implications Findings provide actionable guidance for developing AI policies, professional learning and governance structures that promote transparency, accountability, and equitable access while respecting institutional context. Originality/value This study contributes a multi-stakeholder empirical analysis of AI perceptions within a single institutional context, guided by an integrated conceptual framework to inform ethical policy, governance and practice in higher education.

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