Abstract
Artificial Intelligence (AI) is increasingly integrated into higher education for personalized learning, assessment, and institutional governance. However, challenges of trust, equity, and faculty adoption hinder its transformative potential. This paper develops a conceptual framework for AI infrastructure in education, emphasizing three layers: trust, learning, and governance. Drawing on literature and a case study of an Entrepreneurship College in the Northeastern US, findings suggest that explainability, equitable access, and institutional oversight are critical to enhancing both student learning and faculty confidence.
Recommended Citation
Malik, Mohd Qaiser and Undheim, Trond Arne, "AI Infrastructure for Trust and Learning in Education: The Emergence of The ‘Learning Provenance’ Concept" (2025). NEAIS 2025 Proceedings. 2.
https://aisel.aisnet.org/neais2025/2
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