The governance of public emergencies urgently needs to break the dilemma of the traditional "fragmentation" model. Based on the theory of collaborative governance, this paper constructs a "full-cycle-multi-dimensional" analytical framework, which reveals the core problems such as the imbalance of power and responsibility of multiple subjects, information silos, and institutional lag. Through typical cases such as cross-sectoral collaboration in Guangdong, Hong Kong and Macao Bay Area and precise rescue by X Social Work Service Center, it proposes an organizational structure of "Umbrella Shaped Co-Governance Network" and a balancing mechanism of "Rule of Law-Resilience": constructing a cross-sectoral risk early warning system driven by Artificial Intelligence (AI) beforehand, which can achieve an accuracy of risk prediction up to 82.3%, and transparent scheduling of resources through blockchain technology during the process. Transparent scheduling of resources. AI-driven cross-sectoral risk early warning system is constructed beforehand, transparent scheduling of resources is realized through blockchain technology during the event, and a market-based compensation mechanism is established after the event. The study finds that the improvement of collaborative efficiency requires the activation of social forces through the transfer of data sovereignty and the use of the "meltdown-escalation" law to break the deadlock of cross-sectoral collaboration. The study provides lessons and references for the formulation and implementation of emergency response plans and the optimization of mechanism paths.