As disasters become more frequent and severe, disaster management has increasingly become a global concern, with technological innovation playing a crucial role. The introduction of artificial intelligence (AI) has greatly changed traditional methods of disaster management, opening new avenues for enhancing the efficiency and effectiveness of disaster response. However, despite the transformative impacts of AI in disaster management, there are still some potential issues and challenges that have not been fully explored and addressed. In this review article, we comprehensively review existing research related to AI and disaster management. We selected 5,893 articles from Web of Science and Google Scholar that fit the theme and conducted detailed discussions on the application of different AI technologies in the four stages of disaster management: prevention and mitigation, preparedness, response, and recovery, as well as on disaster technology and ethical issues, through bibliometric analysis and knowledge graph analysis. Based on this, we analysed the core challenges and issues in disaster management where AI has not yet been fully addressed, including pre-disaster and post-disaster resilience enhancement, reinforcement of critical infrastructure, evacuation network planning and design, long-term sustainable recovery after disasters, and related ethical issues in disaster management. We also proposed a future technological research framework. This study provides valuable insights for researchers and practitioners interested in AI and disaster management and clarifies the enormous potential for further research and application of AI in disaster management, potentially driving more progress in this professional community.