2026年数据要素价值释放年：从量变到质变，千亿级蓝海初现雏形

Core Viewpoint - The data factor market is characterized by both "policy system improvement" and "local practice implementation" as it enters 2026, which is designated as the "year of data factor value release" [1] Group 1: Policy and Market Developments - Multiple policy documents focusing on the value extraction of data factors have been issued this year, with local practices advancing simultaneously, such as Shanxi's implementation plan for digital economy development and Jiangsu's completion of the first national "embodied intelligent data set" transaction [1] - The public data products, such as meteorological and statistical analysis data, are expected to mature quickly due to compliance advantages, while financial and healthcare data products will also rapidly form under market incentives [1][4] Group 2: Value Realization of Data Factors - The realization of data factor value relies on both public and enterprise data, with significant potential for value release entering an accelerated phase, supported by the gradual implementation of data infrastructure in 2025 [3] - In 2025, the National Data Bureau published 100 key public data demonstration scenarios covering various industries, leading to effective applications in areas like healthcare and logistics [3] Group 3: Challenges in Data Value Release - The market faces multiple collaborative obstacles that hinder the full release of data value, stemming from a lack of coordinated governance and clear responsibilities among various departments [7] - Issues such as unclear data rights and profit distribution responsibilities in cross-regional data circulation, as well as inconsistent safety standards between industries, impede data sharing [7] Group 4: Future Directions and Recommendations - To facilitate the smooth release of data factor value, addressing collaborative obstacles is crucial, focusing on unifying rules and responsibilities [10] - The establishment of a unified national data market with standardized trading rules and registration systems is essential for transforming data into marketable products [11] - The integration of data infrastructure with artificial intelligence is expected to provide technical solutions for embedding data into business processes effectively [12]