<![CDATA[Artificial intelligence (AI) is increasingly promoted in education, yet its implementation remains uneven, particularly in schools with limited infrastructure. This study examines how school principals manage AI-based learning in infrastructure-constrained settings and how leadership practices are adapted to local realities. The paper aims to analyze the contextual leadership practices of principals in managing AI-based learning in public junior high schools in Aceh Besar, Indonesia, with a focus on vision and local policy, teacher capacity building, infrastructure and resource management, and stakeholder collaboration. Used a qualitative phenomenological design, data were collected through semi-structured interviews, field notes, school documents, and limited observation, and were analyzed using six stages of thematic analysis. The findings reveal four interrelated patterns: AI was positioned as a practical tool rather than a systemic transformation; teacher capacity was developed mainly through internal, practice-based learning; infrastructure limitations shaped adaptive strategies such as offline materials and shared device use; and collaboration with teachers, parents, and school committees became an essential support mechanism. These findings showed that AI implementation in constrained environments does not follow a linear digital transformation model but evolves through incremental, context-driven adaptation. The study concludes that principal leadership in such settings is best understood as contextualized AI leadership, in which infrastructural limitations, teacher capacity, and social capital are integrated into a responsive and sustainable leadership approach.]]>
Copyrights © 2026
