Urban flooding presents a growing threat to cities globally, intensified by climate change, rapid urbanization, and socio-spatial inequality—especially in the Global South. In response, Artificial Intelligence (AI) is increasingly heralded as a transformative tool for climate adaptation, offering new possibilities for flood forecasting, risk mapping, and adaptive planning. However, despite its technical promise, AI’s integration into urban flood adaptation remains uneven, contested, and fraught with socio-political implications. This review chapter critically examines the conceptual, empirical, and practical intersections of AI and urban flood adaptation, synthesizing literature across the fields of urban studies, disaster risk reduction, and AI ethics. The analysis reveals key synergies, such as improved predictive accuracy and real-time scenario planning, alongside contradictions, including algorithmic opacity, data-driven exclusions, and the marginalization of informal settlements. The review challenges dominant techno-managerial narratives by repositioning AI as a governance actor embedded within systems of power and knowledge. Drawing on climate justice, Southern urbanism, and techno-governance theories, the chapter calls for co-produced, context-sensitive, and ethically accountable AI approaches in flood adaptation. It concludes by outlining future research directions and policy recommendations aimed at ensuring that AI enhances—not undermines—equity and resilience in urban adaptation strategies.