Generative artificial intelligence (GenAI) represents a major leap forward in AI technology, offering the potential to reshape education in various aspects. This paper explores the transformative potential of GenAI in geography education, focusing on its impacts across curriculum, pedagogy, assessment, and fieldwork, through the lens of the Substitution, Augmentation, Modification, and Redefinition (SAMR) model. In curriculum development, GenAI enables automatic generation and personalization of geographic content. Pedagogical approaches are evolving from text-based instruction to data-driven learning experiences where students analyze geographic phenomena using GenAI tools. Assessment methods are shifting to adaptive evaluation systems with continuous feedback, while fieldwork benefits from real-time data processing and opportunities for global collaboration. Nevertheless, these advancements are accompanied by substantial risks, including challenges such as overreliance on AI, content inaccuracies, biases, and data privacy concerns.