Teacher Leadership and Artificial Intelligence Revolution: Narratives of Teachers Working in Deprived South African School Contexts

Abstract

The rapid development of artificial intelligence (AI) is transforming teaching, learning and teacher professionalism, yet limited attention has been given to how teachers experience and exercise leadership while navigating AI in deprived school contexts. This study aimed to explore how teachers experience, interpret and enact teacher leadership, agency and professional identity amid the AI revolution in resource-constrained schools. The study adopted an interpretivist paradigm and qualitative approach, using a narrative inquiry design. Six teachers from deprived school contexts were purposively selected. Data were collected through semi-structured individual interviews and field notes and analysed using Braun and Clarke’s reflexive thematic analysis. Freire’s Critical Pedagogy provided the theoretical lens for interpreting teachers’ experiences. The findings revealed five interconnected themes: AI is reshaping teacher leadership; AI reinforces educational inequalities; AI influences teacher agency and professional identity; limited digital infrastructure constrains AI integration; and teachers demonstrate agency and resilience through collaboration, improvisation and knowledge sharing. Teachers increasingly assume informal leadership roles as technology mentors, knowledge sharers and facilitators, while structural constraints, including unreliable electricity, limited connectivity, inadequate devices and insufficient professional development, restrict meaningful AI integration. The study recommends AI professional development that integrates technical, pedagogical, ethical and leadership competencies, alongside investment in digital infrastructure, affordable connectivity and collaborative teacher-learning communities. The paper contributes a contextually grounded understanding of teacher leadership in the AI era by foregrounding teachers’ narratives from deprived school contexts. It extends existing AI-in-education scholarship beyond adoption and readiness by demonstrating how teacher agency, leadership and professional identity are negotiated within conditions of technological inequality