Abstract: The rapid advancement of artificial intelligence has increased the complexity of data governance, making multimodal data governance a key approach to addressing these challenges, and calling for a clear articulation of its core issues and governance pathways. Building on a conceptual analysis of multimodal data governance, this study focuses on the governance challenges emerging from the interaction between multimodal data characteristics and AI environments. From the dual perspectives of technological innovation needs and cybersecurity incidents, the study systematically analyzes the internal mechanisms and external manifestations of these issues in terms of their causes and consequences. Accordingly, this study proposes a multimodal data governance pathway in  AI environments that takes value co-creation as the core objective, technological regulation as the key instrument, and a coordinated soft-and-hard regulatory framework as the central model. The findings offer a reference for improving data governance frameworks in AI environments.