Artificial Intelligence in Teacher Education: A Comparative Perspective

Background and Objectives: Artificial Intelligence (AI) has become a transformative force, reshaping educational paradigms. Teacher education systems, as the foundation for preparing future educators, are directly impacted by these changes. This study explores the comparative applications of AI in enhancing teaching methods and instructional content in teacher training programs. Methods: A systematic review was conducted based on PRISMA guidelines. Articles published between 2020 and 2025 were retrieved from ScienceDirect, Springer, IEEE, and SID databases. After applying inclusion and exclusion criteria, 27 studies were selected for analysis.Findings: Findings were classified into five areas: (1) developing AI literacy and digital competencies of teachers, (2) personalizing learning and providing intelligent feedback, (3) employing generative AI in content creation and instructional design, (4) assessing teaching performance through data-driven analytics, and (5) addressing ethical and infrastructural challenges. The comparative analysis revealed that advanced systems emphasize critical and ethical competencies, while contexts such as Iran focus more on technological and infrastructural aspects. Conclusion: AI has strong potential to transform teacher education through adaptive instruction, enriched content, and accurate assessment. Achieving this potential requires investment in AI literacy, ethical frameworks, and integrated ecosystems. A holistic pedagogical approach, beyond instrumental use, is essential in shaping teacher education policies.