Responsible AI Governance for Student-Centred Digital Transformation in Higher Education

Abstract

The digitalisation of higher education as well as the recent advances in generative and agentic artificial intelligence (AI) are transforming teaching and learning, academic leadership, institutional governance and student support services. AI-enabled technologies provide opportunities to personalise learning, improve educational decision-making, enhance administrative efficiency and foster innovation across universities. However, their widespread adoption also raises concerns regarding their algorithms’ transparency, explainability, fairness, accountability, privacy, academic integrity and stakeholder trust. Consequently, responsible AI governance is emerging as a strategic institutional capability that facilitates student-centred digital transformation while safeguarding ethical, educational and societal values. This conceptual paper examines how responsible AI governance can support higher education institutions in fostering digital transformation within an increasingly complex technological and regulatory environment. Building on recent advances in AI governance and explainable artificial intelligence (XAI), it proposes a conceptual framework that integrates governance mechanisms with institutional capabilities to promote transparent, trustworthy and student-centred AI adoption. The framework synthesises principles of ethical oversight, algorithmic transparency, explainability, risk management, regulatory compliance, stakeholder engagement, human oversight, and continuous evaluation. It argues that explainability should be regarded as an institutional capability that empowers educators, supports informed student engagement, strengthens academic decision-making and reinforces institutional legitimacy. The proposed framework demonstrates how responsible AI governance can enhance strategic alignment, organisational learning, interdisciplinary collaboration, knowledge sharing and digital resilience while supporting equitable educational innovation. It also considers the implications of AI for curriculum design, assessment, student engagement, academic work and human-AI collaboration. This contribution extends the literature on responsible AI in a higher educational context. It offers practical guidance for university leaders, educators, policymakers and quality assurance bodies who are seeking to implement trustworthy AI systems that strengthen institutional effectiveness and promote student-centred digital transformation. Therefore, it supports the achievement of SDG 4 (Quality Education) and SDG 9 (Industry, Innovation and Infrastructure) by advancing responsible AI governance and digital innovation in higher education.