Sustainable Geospatial Artificial Intelligence (GeoAI) in human geography focuses on enhancing reproducibility, replicability, and expandability (RRE) to ensure reliability, scalability, and impact in geospatial research and applications. Achieving RRE is essential for verifying, extending, and applying geospatial findings across various contexts and scales. This chapter discusses the significance of RRE in GeoAI, highlighting how these principles contribute to sustainable outcomes in urban planning, agriculture, and public health. It explores the current advancements and challenges in implementing RRE within GeoAI, such as the complexity of workflows, scalability issues, and ethical considerations. By addressing these challenges, we aim to establish a framework for sustainable GeoAI that supports reliable, scalable, and equitable development across diverse domains.