This article examines the application of Quality management principles to learning in the age of AI and digital transformation. The traditional model is considered to be inadequate in coping with modern challenges associated with AI deployment due to concerns of privacy, transparency, and measurement of outcomes. A conceptual model that is effective and addresses the concerns should be underpinned by guidelines such as ISO/EIC 42001, OECD, UNESCO, IEEE P7001, and NIST AI RMF 2023 promote transparency, integrity, human oversight, and robustness of AI systems in learning ecosystems. Implementation of the conceptual framework contributes towards better ethical compliance by integrating ethical oversight, promotes trust while reinforcing the adoption of AI within learning environments, and positive culture of continuous improvement.