A digital twin is defined as the virtual representation of the real world, encompassing materials, objects, processes and relationships. Digital twins can be used to safely and economically test various scenarios before implementing them in real-life situations. The geospatial data collected with sensors, GPS (Global Positioning System), satellite data and IoT, can be analysed with AI (Artificial Intelligence) and ML (Machine Learning) algorithms. The Geographic Information System (GIS) is used for data integration, real-time visualisation of the model, analysis and estimation of future projections. The geospatial digital twin is being updated regularly with the implementation of GIS. Geo-AI is the application of AI using geospatial data and technology to enhance understanding of the real-world. GeoAI leverages AI techniques, such as machine learning to process, analyse and extract patterns, trends and correlations. GeoAI has applications in several fields, such as agriculture, forestry, water, environmental monitoring, urban planning, disaster management, transportation planning, and monitor traffic, and air pollution to enhance public safety.