In the era of an intelligent society, artificial intelligence drives the transformation of network ecosystem governance from the Internet ecosystem governance paradigm to the digital intelligence ecosystem governance paradigm. Based on the five-ring analysis framework of “medium transformation—structural reorganization—cognitive perturbation—order adaptation—ecosystem restoration”, this paper systematically explains the mechanism by which AI drives the transformation of the network ecosystem governance system; identifies the main challenges in the Chinese context, and proposes corresponding countermeasures. The study shows that AI first alters the medium for generating content and actions, then reorganizes platform attention structures, further influences public factual judgment, emotional responses, and value identification, and ultimately requires governance targets to expand from end-stage content to encompass data, algorithms, models, platforms, and intelligent agents, ultimately pointing toward ecosystem restoration in terms of factual recovery, rights relief, and institutional learning. However, China also faces challenges such as difficulties in identifying the sources of generated content, amplification of platform structural risks, disruption of the foundation of public facts, insufficient alignment of institutional rules, and weak resilience in ecosystem restoration. To address these challenges, China’s governance approach should, under the guidance of Party leadership, people-first principles, adherence to principles while innovating, legal safeguards, and a systemic perspective, incorporate international experiences such as risk classification, systemic risk assessment, organizational risk management, and front-end security design to establish a governance system that links generated content identification and model evaluation, platform systemic risk assessment, qualitative public facts, classified and tiered supervision, ecosystem restoration, and international rule cooperation.