AI Literacy for Teacher Development: Challenges and Pathways in Developing and Underdeveloped Contexts

Artificial Intelligence (AI) gradually alters educational practice, presenting new demands to the pedagogical, ethical, and professional skills of teachers. However, the overall research about AI literacy and its role in teacher development is predominantly focused on the developed context, thus limiting our understanding of the challenges facing such teachers in developing and underdeveloped societies. To fill this gap, this paper conducts a critical thematic review of empirical studies, conceptual literature, and policy-focused studies published since 2019. The review puts together key challenges, including infrastructural barriers, limited accessibility to continuous professional development, the lack of pedagogical preparation, ethical and equity challenges, and inadequate policies. In addition to this, it outlines new directions, such as context-specific professional development models, scalable virtual learning platforms, equity-focused frameworks, and human-AI collaborative strategies. The review redefines teacher development as a kind of professional agency operating on the concept of AI literacy as the convergence of technical knowledge, pedagogical acuity, and critical ethical awareness. The study also emphasizes the importance of strengthening institutional support, policy coordination, and collaborative professional learning environments to foster sustainable AI literacy development among teachers. The results offer practical lessons on enhancing equitable, sustainable, and context-based AI adoption in contemporary education systems globally.