Keyword: education governance

ABSTRACT: The development of artificial intelligence in education has outpaced the institutionalisation of policies governing its use, accountability, and implementation. Cross-national scholarship remains dominated by discussions of adoption, pedagogical opportunities, and ethical risks, while variation in policy enactment across national education systems remains underexplained. This study examines artificial intelligence policy enactment in Indonesia, Finland, and South Korea through a comparative qualitative policy analysis of 22 core and supporting policy documents. The analysis focused on policy orientation, the locus of enactment authority, regulatory-ethical institutionalisation, and implementation mode. The findings show that the main differences across the three systems do not lie in technology adoption itself, but in the logic through which policy is enacted. Indonesia demonstrates capacity-led enactment shaped by gradual implementation and teacher capacity building. Finland demonstrates regulatory-literacy enactment mediated by education providers and structured through regulation, ethics, and AI literacy. South Korea demonstrates scaled rollout enactment driven by state direction, infrastructure support, and personalised learning reform. The study proposes a three-part typology comprising capacity-led enactment, regulatory-literacy enactment, and scaled rollout enactment, and argues that cross-national variation in artificial intelligence policy in education is best explained through the arrangement of authority, regulatory-ethical institutionalisation, and implementation instruments.

ABSTRACT: Artificial intelligence (AI) is rapidly reshaping school leadership within Education 4.0, offering enhanced decision-making and organisational efficiency while intensifying ethical concerns regarding transparency, bias, and accountability. Existing research has largely treated these opportunities and risks as separate phenomena, overlooking the relational processes through which AI is enacted in practice. This paper advances a process-based conceptualisation by positioning trust as the central mediating mechanism in AI-enabled school leadership. It argues that AI does not produce outcomes directly; rather, its effects are contingent on how it is accepted, interpreted, and enacted within school contexts. The proposed framework shows that trust shapes whether AI leads to constructive outcomes, including ethical use, professional engagement, and improvement, or to disruptive consequences such as resistance and mistrust. Leadership is conceptualised as a key antecedent of trust, highlighting the centrality of relational governance in the effective and responsible integration of AI in schools.