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and data analytics. More recent work explores AI applications such as intelligent tutoring
systems, automated assessment, and learning analytics. However, these studies primarily
address pedagogical innovation, while the governance implications of AI-enabled
educational ecosystems remain underexplored.
Current literature also tends to treat governance issues separately. Data
governance, platform coordination, and AI ethics are often discussed in isolation, leading
to fragmented perspectives. As universities rely on integrated digital systems, there is a
need for frameworks that explain how academic training governance systems adapt to AI-
driven environments.
To address this gap, this study develops a conceptual framework for restructuring
academic training governance in the AI era. Drawing on institutional theory and digital
governance, it proposes a four-pillar model: data governance, digital platform governance,
data-driven decision-making, and AI ethics governance. Together, these pillars explain
how universities transition from administrative models to AI-enabled academic training
governance.
The remainder of this paper is organized as follows. Section 2 reviews the literature
on digital transformation, AI in academic training governance, and institutional and digital
governance perspectives. Section 3 presents the conceptual framework. Section 4
discusses its implications, Section 5 outlines policy and institutional implications, and
Section 6 concludes the paper.
This study standardizes key terms to ensure conceptual clarity. Academic training
governance refers to the governance of teaching, curriculum, and student-related
academic processes. Digital governance is used as an overarching concept describing the
governance of digital systems at the institutional level, while digital platform governance
refers specifically to the coordination of interconnected digital infrastructures. Digital
infrastructures denote technical systems such as learning management and information
systems, whereas digital ecosystems refer to the broader institutional environment in
which these systems operate.
2. Literature review
2.1. Digital transformation in higher education
Digital transformation is a central feature of contemporary higher education, as
universities integrate digital technologies into teaching, learning, and institutional
management. Digital infrastructures such as learning management systems, online
platforms, and student information systems enable more flexible and accessible learning
environments, supporting online, blended, and hybrid models (Bond et al., 2018; Selwyn,
2021).
Beyond pedagogy, digital transformation reshapes academic processes and
institutional operations. Digital systems allow universities to collect and analyze data on
student engagement, learning performance, and course participation, providing insights
for curriculum development, student support, and institutional planning (Zawacki-Richter
et al., 2019). As a result, digital technologies influence not only teaching practices but also
organizational structures and governance mechanisms.
Importantly, digital transformation extends beyond technology adoption. It involves
restructuring organizational processes and governance systems to support integrated
digital environments (Bates, 2015). Universities must develop capabilities to manage
digital infrastructures and coordinate information systems across academic and
administrative units.

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