AI Literacy Among Pre-Service Teachers: A New Dimension of Teacher Professional Development

The rapid diffusion of artificial intelligence (AI) technologies — including generative tools, intelligent tutoring systems, and adaptive learning platforms — is reshaping the teacher–student relationship into a teacher–AI–student dynamic (UNESCO, 2024). Despite this shift, teacher education programmes have been slow to embed AI literacy as a core professional competency, leaving pre-service teachers to enter classrooms with fragmented and largely self-acquired understanding of AI. Purpose: This review synthesises conceptualisations and empirical evidence on AI literacy among pre-service teachers and positions it as an emerging, distinct dimension of teacher professional development. Review methodology: Following a systematic narrative-review protocol, fifteen peer-reviewed studies published between 2020 and 2025 were retrieved from Scopus, Web of Science, ERIC, Frontiers, and Elsevier/Springer databases and analysed thematically alongside foundational policy documents (UNESCO, NEP 2020). Major findings: Pre-service teachers generally demonstrate moderate AI awareness and ethical sensitivity but weaker pedagogical-integration and problem-solving competencies; structured, TPACK-aligned coursework produces measurable gains, though most evidence remains cross-sectional and geographically concentrated. Practical implications: Teacher-education institutions, particularly those regulated by India's National Council for Teacher Education, require embedded — rather than elective — AI-literacy modules, faculty capacity-building, and revised practicum assessment. Conclusion: AI literacy should be formally recognised as a fourth pillar of teacher professional development alongside content, pedagogical, and technological knowledge, warranting coordinated policy, curricular, and institutional action.