Determinants of Teachers’ Adoption of Artificial Intelligence: Evidence from Kazakhstan

Abstract

In the context of accelerated digitalization of education and national initiatives for the introduction of artificial intelligence (hereinafter – AI) in Kazakhstan, the study aims to identify the factors determining the adoption of AI by teachers. This study examines the determinants of teachers’ adoption of AI in Kazakhstan, a context where empirical evidence remains limited despite growing national emphasis on AI integration in education. Drawing on survey data from 662 teachers across diverse regions, the study investigated how demographic factors, professional qualifications, ICT training, self-efficacy, and resource availability influence AI use in classrooms. Results indicate that younger teachers are significantly more likely to use AI, whereas qualification level did not affect use. Formal ICT training during university education emerged as a strong positive predictor of adoption, and initial confidence with ICT was modestly associated with AI use. Age was a statistically significant predictor (F = 3.72, p = 0.0054): teachers aged 20-39 are more likely to use AI (M = 2.18) than teachers in older age groups (M = 1.82). On the contrary, the presence of ICT education in higher education significantly increased AI use (U = 48,209.5, p = 0.0015). By contrast, gender, subject specialisation, school location, and language of instruction did not yield meaningful differences. The findings highlight that while AI adoption among Kazakhstani teachers is growing, its use remains selective rather than routine. The study concludes that embedding structured ICT preparation in teacher education and providing sustained professional.