Climate change has become a major problem to the populations in the coast of the United States and the rising sealevels; extreme weather conditions and floods are threatening the lives and infrastructure. Although the risks havebeen raised, there is still a lack of scalable, real-time, data-driven structures to support climate adaptation, as well asimprove community resilience. The article discusses the opportunity of AI-driven predictive analytics to deliveruseful information in climate adaptation on vulnerable coasts. With the combination of machine learning models,geospatial data, and real-time environmental data, AI is able to enhance the accuracy of the climate risks predictionand enable more effective decision-making processes. This paper focuses on AI-based flood risk managementsystems, early warning, and distribution of resources on coastal communities. Results show that AI models have thepotential to become important in terms of timeliness and accuracy of predictions, enabling communities to executeadaptive actions and enhance overall insights to climate-related dangers. Nevertheless, including data privacy,model accuracy, and the necessity to collaborate across sectors are still present. The article ends with the realizationof the significance of scalable AI platforms to promote climate resilience in coastal areas and proposes the directionof future research to expand the role of AI in climate action