Core Insights - The fourth Global Digital Trade Expo was held in Hangzhou, featuring the 2025 Global Data Management Summit focused on "Data × Artificial Intelligence" [1] - Zhongdian Jinxin presented cutting-edge thoughts and practical results in the integration of data governance and AI [1] Data Governance New Paradigm - Du Xiaozheng from Zhongdian Jinxin emphasized the need for a new data governance system in the era of large models, highlighting the importance of unstructured data processing and deep integration of AI and data [4] - The proposed "One Lake, Two Repositories" architecture aims to support comprehensive data asset construction and AI applications [4] - The upgraded Yuanqi Data Asset Platform focuses on "intelligent agent-driven" collaboration, enhancing data accuracy to over 95% [4] Challenges in Data Governance - The financial industry faces common challenges such as difficulties in processing unstructured data and immature cross-domain collaboration mechanisms [5] - The need for high-quality data is critical for the intelligent upgrade of data governance systems [5] AI-Driven Data Governance Practices - A forum co-hosted by Zhongdian Jinxin and CCF Digital Finance Association discussed innovative data governance paths in the financial sector under AI [8] - Experts emphasized the importance of ensuring AI models are verifiable, auditable, and traceable, advocating for tailored regulatory approaches [8] Innovations in Data Governance - Zhang Fang from Postal Savings Bank of China highlighted the emergence of a new data governance paradigm driven by large models, focusing on six core areas of data governance [9] - The shift from passive response to proactive foresight in financial data governance was discussed, emphasizing the integration of technology and scenarios [9] Roundtable Discussion on AI and Data Governance - Experts discussed the transformation of data governance systems through AI, addressing challenges such as data rights and ethical compliance [12] - The transition from manual governance to AI-driven autonomy was emphasized, with AI seen as a key tool for sustainable data governance [12] Future Directions - The need for a new generation of governance systems that include AI-generated data was highlighted, aiming to transform data from a resource into a true asset [12] - The discussion outlined an evolutionary path for data governance from "responding to challenges" to "restructuring pathways," ultimately aiming for autonomy [13]