Managing the Institutionalization of AI Governance in Higher Education: A Technology–Organization–Environment Analysis
TL;DR
Investigating the institutionalisation of GenAI governance through a management-oriented qualitative document analysis of three documents indicates that GenAI governance becomes institutionalised not solely through policy formulation, but through organisational capacity to translate technological change into assigned responsibilities, coordinated structures, and sustained oversight.
Abstract
Generative artificial intelligence (GenAI) has emerged as a significant governance concern for higher education institutions, necessitating attention to responsible technology use, organisational capability, governance structures, resources, and ongoing oversight. This study investigates the institutionalisation of GenAI governance through a management-oriented qualitative document analysis of three documents from a focal higher education institution. Using the Technology–Organization–Environment (TOE) framework, the study identifies governance commitments articulated in the institution's AI policy and examines the technological, organisational, and environmental conditions influencing these commitments. The analysis employs a 13-construct TOE codebook to examine the institution's GenAI policy, the establishment of its responsible AI committee, and an earlier memorandum on AI in teaching and learning. The results demonstrate that the institution's governance response evolved through a progression from capability development to the establishment of formal governance structures and policy formalisation. Technological conditions created opportunities and practical requirements for GenAI governance, while organisational conditions—particularly leadership, structure, competence, resources, and readiness—were most extensively documented. Environmental conditions primarily defined regulatory and institutional boundaries. The findings indicate that GenAI governance becomes institutionalised not solely through policy formulation, but through organisational capacity to translate technological change into assigned responsibilities, coordinated structures, and sustained oversight. This study advances higher education management and AI governance by extending the TOE framework to institutional governance and by identifying a capability–structure–formalisation pattern for understanding how AI governance becomes embedded within university organisational arrangements.