Paper Type
ERF
Abstract
Integrating Artificial Intelligence (AI) in higher education presents opportunities and challenges, particularly regarding equity, access, and ethical implementation. While AI-driven learning environments can enhance personalised education, they risk exacerbating digital divides due to disparities in AI access, literacy, and institutional policies. This study investigates these equity-related challenges within a New Zealand university’s Information Systems department, employing Activity Theory as a framework to examine the systemic factors influencing AI adoption. Using a mixed-methods approach, the study will collect qualitative and quantitative data over two years, incorporating interviews, focus groups, surveys, and experimental assessments. Preliminary findings highlight unequal AI access, gaps in AI literacy, and inconsistent institutional policies, reinforcing the need for structured AI literacy programmes and equitable governance frameworks. The study intends to contribute theoretically by extending Activity Theory to AI equity research and offer practical recommendations for universities to ensure fair, inclusive, and responsible AI adoption in education.
Paper Number
1782
Recommended Citation
Perera Muthupoltotage, Udayangi and Gardner, Lesley A., "The Challenge of Equitable AI Adoption in Higher Education: Literacy and Access" (2025). AMCIS 2025 Proceedings. 22.
https://aisel.aisnet.org/amcis2025/is_education/is_education/22
The Challenge of Equitable AI Adoption in Higher Education: Literacy and Access
Integrating Artificial Intelligence (AI) in higher education presents opportunities and challenges, particularly regarding equity, access, and ethical implementation. While AI-driven learning environments can enhance personalised education, they risk exacerbating digital divides due to disparities in AI access, literacy, and institutional policies. This study investigates these equity-related challenges within a New Zealand university’s Information Systems department, employing Activity Theory as a framework to examine the systemic factors influencing AI adoption. Using a mixed-methods approach, the study will collect qualitative and quantitative data over two years, incorporating interviews, focus groups, surveys, and experimental assessments. Preliminary findings highlight unequal AI access, gaps in AI literacy, and inconsistent institutional policies, reinforcing the need for structured AI literacy programmes and equitable governance frameworks. The study intends to contribute theoretically by extending Activity Theory to AI equity research and offer practical recommendations for universities to ensure fair, inclusive, and responsible AI adoption in education.
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