BEYOND DIGITAL COMPETENCE: ARTIFICIAL INTELLIGENCE AS A CATALYST FOR TRANSFORMING TEACHER EDUCATION AFTER COVID-19

Abstract

The COVID-19 pandemic accelerated the integration of digital technologies in education, positioning Artificial Intelligence (AI) as a transformative force in teacher education. Moving beyond conventional digital competence, AI enables personalized learning, intelligent assessment, adaptive feedback, learning analytics, and data-driven instructional decision-making. This review synthesizes recent evidence from systematic reviews, empirical studies, and policy documents to examine AI's role in reshaping post-pandemic teacher education. The findings indicate that teacher preparation is evolving toward developing AI literacy, pedagogical adaptability, ethical awareness, and data literacy. While AI enhances instructional planning, assessment, and professional development, challenges such as algorithmic bias, data privacy, academic integrity, unequal access, and inadequate teacher preparedness remain significant. The review emphasizes that successful AI integration requires curriculum redesign, continuous professional development, supportive institutional policies, and responsible governance. It concludes that AI should complement rather than replace teachers, preparing educators to create ethical, inclusive, and learner-centred educational environments capable of meeting the evolving demands of twenty-first-century education.