Cultivating university data culture in the age of artificial intelligence: a conceptual framework and critical reflections

Abstract

Introduction. This paper examines the transformation of university data culture in the age of AI. AI and big data are reshaping how universities manage data, make decisions, and interact with stakeholders, raising both opportunities and challenges.

Method. The study explores the concept of university data culture, proposing a four-layer conceptual framework: the data layer, user layer, organizational layer, and societal layer.

Analysis. The four-layer framework captures the lifecycle of data, stakeholder behaviours and competencies, institutional policies, and societal influences. It emphasizes how AI transforms data usage and governance within universities, as well as the ethical and social considerations that arise.

Results. AI is driving a shift from traditional data management to structured data governance, fostering greater data-informed decision-making, and encouraging bottom-up participation among faculty and students. However, challenges related to ethics, privacy, and inequality persist.

Conclusions. The transformation of university data culture is not just technological but cultural, requiring universities to address ethical and social issues. Ensuring inclusivity, fairness, and responsibility in data practices is critical for fostering a balanced and sustainable data culture in higher education.