Artificial Intelligence Integration in Teaching and Governance in the United Arab Emirates (UAE) Schools: Basis for Framework Development

Artificial intelligence (AI) adoption in schools creates opportunities for instructional innovation but also raises questions concerning governance, professional judgement, and institutional readiness. This study examined AI integration and governance in selected United Arab Emirates (UAE) schools and developed a leadership-guided implementation framework. An exploratory sequential mixed-methods design combined semi-structured interviews with 10 purposively selected teachers and school leaders and a subsequent structured survey of 80 respondents, selected through stratified sampling. Interview transcripts underwent thematic analysis; quantitative responses were analysed using weighted means, standard deviations, and Pearson product–moment correlations at the .05 significance level. Seven qualitative themes clustered into AI integration and AI governance. Overall AI integration was rated moderate (grand weighted mean [GWM] = 3.41), with adaptive integration highest (3.76), followed by professional productivity (3.38) and AI-enhanced teaching (3.08). Overall AI governance was high (GWM = 3.32), led by ethical governance (3.66), followed by strategic governance (3.34), organisational support (3.34), and uneven governance (2.97). Organisational support was significantly associated with all three AI-integration dimensions, while adaptive integration had its strongest observed association with ethical governance (r = .539, p < .001). Integrated findings informed the proposed Leadership-Guided AI Integration and Governance Framework for UAE Schools, emphasising pedagogical use, human oversight, ethical safeguards, strategic leadership, professional learning, and institutional readiness. The proposed framework is a study-derived practical output, not a causally validated model.