The exponential population density of the urban area and diversification of the urban landscape require more adaptive ideas in addressing infrastructural development. This book chapter scrutinizes the centrality of geographic information systems and artificial intelligence in infrastructure development with reference to smart and sustainable cities. There are many ways in which Geospatial big data can be used in the smart urban planning process, particularly when AI is incorporated into the information system where such elements as transport infrastructure, utilities and public services are concerned. This chapter seeks to describe how different technologies such as Geographic Information Systems (GIS), remote sensing, and spatial databases afford accurate spatial data that is central to depicting, evaluating and managing the physical fabric of urban systems. Furthermore, the overall use of AI methodologies such as machine learning and predictive analysis is also described as a way to enhance different decision-making procedures, identifying growth trends in cities, as well as resource management. Analyzing case studies and examples the chapter shows how integrated geospatial technologies and AI can deliver advancement in urban infrastructure to enhance efficiency, sustainability and resilience. Also, it describes the vulnerabilities and restrictions inherent to such technologies as well as data protection issues, interdisciplinarity of smart city implementation, and the call to mind inequality in terms of Smart City services provision. After reading this chapter, the reader will have a clear perception of innovative approaches, based on geospatial technologies and AI that are enhancing urban infrastructure planning and contributing towards smart cities.