Artificial Intelligence in Teacher Professional Development: A Systematic Review

This systematic review synthesizes empirical evidence on the use of artificial intelligence (AI) in teacher professional development (TPD), focusing on how AI is conceptualized, which technologies are used, and which effects on teaching and learning are reported. Following PRISMA guidelines and a preregistered protocol, 3,406 records were identified across four databases. After screening and quality appraisal, 21 empirical studies published between 2022 and 2025 were included. The results show that most studies conceptualize AI as a learning objective in TPD, aiming to enhance teachers’ AI literacy, knowledge, self-efficacy, and readiness for classroom integration. Fewer studies conceptualize AI as a pedagogical tool within TPD, primarily using language-based AI systems to provide individualized feedback, scaffold reflection, or support practice-based learning. Across studies, predominantly positive effects are reported at the teacher level, including gains in AI-related knowledge and competencies, improved attitudes and motivation, and changes in instructional practices. Evidence on student-level outcomes is rare and limited to a single study reporting small positive effects. Methodologically, the literature is dominated by small-scale, short-term, and exploratory designs, with limited use of control groups and little longitudinal evidence. Geographically, research is heavily concentrated in a small number of countries, particularly the United States. Overall, the findings indicate promising effects of AI-supported TPD, while also revealing substantial gaps regarding methodological rigor, sustainability of effects, and transferability across educational contexts.