Artificial Intelligence in Teacher Education: A Systematic Literature Review of Pedagogical Frameworks, Empirical Evidence, and Ethical Implications (2020–2026)

Generative artificial intelligence is invading teacher education before the profession has reached consensus on preparing teachers to use it. This scoping review explores the pedagogical frameworks that shape AI integration initiatives, the evidence on pre-service teachers’ and teacher educators’ experiences, and ethical implications. A PRISMA-inspired search of open databases detected seven sources of information published between January 2020 and October 2026. Three framework articles and five empirical studies (one of which is mixed methods) were included. Frameworks extended technology pedagogical content knowledge and emphasized competency modeling in which ethical considerations are viewed as integral to pedagogy. Empirical studies, predominantly small-scale and cross-sectional, reported varying levels of adoption, heavy focus on ideation, and overconfidence in one’s ability to critique AI. Ethics was broadly acknowledged but seldom taught or assessed systematically, and none of the studies evaluated pupils’ learning outcomes. The review finishes by suggesting research priorities and design principles for programs.