Technological Implementation: AI Adoption in Kerala CBSE Schools Amid Systemic Barriers

Abstract

This sequential explanatory mixed-methods study investigated Artificial Intelligence (AI) adoption among Central Board of Secondary Education (CBSE) teachers in Kerala, India (N= 106). Drawing on the Technology Acceptance Model and UNESCO's human-centred AI framework, the study examines teacher motivation moderated by ecosystem constraints. A four-stage integration pathway (Awareness-Efficiency-Augmentation Transformation) is proposed to guide equitable implementation.
Survey results revealed a pronounced awareness–practice gap: while 75.1% of teachers (80/106) reported understanding AI's educational potential, only 28.3% (30/106) said they used it regularly in classrooms—a 46.8 percentage-point difference. Adoption patterns highlighted systemic inequities, with a disparity between urban private schools (64.3%, 9/14) and rural government schools (7.7%, 1/13). Teachers identified three interconnected barriers: infrastructural precarity (77% in rural government schools, 10/13), insufficient practice-oriented training (62% overall, 66/106), and the absence of school-level AI governance frameworks (77%, 82/106). Qualitative interviews (n = 20), analysed through reflexive thematic analysis, generated four explanatory themes: infrastructural precarity, training-to-practice disconnect, ethical uncertainty, and cautious optimism. Findings challenge deficit-oriented narratives of teacher resistance and argue that AI integration in developing contexts requires coordinated investment in infrastructure, professional development, and governance reform aligned with National Education Policy 2020 priorities.