Developing teacher AI competence: A systematic review of beliefs, professional learning, and cultural factors

Teacher AI competency is shaped by a complex interplay of individual, institutional, and cultural forces. This systematic review integrates existing teacher AI competency frameworks with Gibson et al.’s three-level theory of learning to examine how beliefs (micro), professional learning (meso), and cultural influences (macro) shape competency development. We identified and analysed 42 empirical studies (2015–2025) involving pre-service and in-service teachers engaged in both AI Education and AI in Education. A 6 × 3 matrix crossing six competency dimensions with three sociocultural levels guided inductive and deductive coding. The review identifies five key belief dimensions, four observed professional development approaches, and five cultural factors. Cross-group patterns show that career stage, subject culture, and regional context shape distinct developmental pathways for teacher AI competency. The review argues for integrated, contextually responsive professional learning pathways that move beyond technical training to address identity formation, disciplinary norms, and structural conditions in building teacher AI competency.