Coral reefs represent one of Earth’s most diverse and sensitive marine ecosystems, yet their global distribution and ecological stability are increasingly threatened by climate change and human pressures. A biogeographic perspective provides insight into how environmental parameters such as temperature, salinity, water clarity, depth, and nutrient regimes shape the spatial distribution, diversity, and resilience of reef systems across regions including the Indo-Pacific, Red Sea, Caribbean, and Great Barrier Reef. Recent advances in artificial intelligence (AI) are transforming coral reef science by enabling high-resolution mapping, automated species identification, ecosystem monitoring, and predictive modelling. Using satellite, drone, acoustic, and in-situ sensor datasets, AI methods—including convolutional neural networks, recurrent neural networks, Random Forests, and habitat suitability models—enable classification of coral types, detection of bleaching, evaluation of reef health, forecasting of future distribution shifts under climate scenarios, and design of optimized marine protected areas. Sensitivity and scenario-based analyses further identify key environmental drivers of resilience. By integrating multi-source data streams and enabling adaptive early-warning systems for bleaching, invasive species, and pollution, AI offers a powerful framework for future-focused coral conservation. This chapter highlights how AI-assisted biogeography can accelerate early diagnostics, improve decision support, and strengthen restoration and management strategies to safeguard coral reef biodiversity in a rapidly changing ocean.