Guotai Haitong: Institutional closed-loop superimposed AI catalysis is ready to embrace the "value release year" of data elements.

Guotai Haitong released a research report stating that from December 29th to 30th, 2025, the National Data Work Conference was held in Beijing. The conference focused on clarifying the functional positioning of data circulation service agencies, improving the efficiency of data circulation and transaction services, and promoting the prosperity of the data market ecosystem. It was specially deployed around these topics and clearly stated that 2026 would be the "year of releasing the value of data elements". It emphasized the need to focus on facilitating data flow and resource allocation channels, activating data market supply and demand, prospering the market ecosystem, further promoting data accessibility, flow, effective usage, and security, and promoting the comprehensive integration of data elements into the process of economic value creation to better empower economic and social development. Guotai Haitong expressed that with the combination of institutional closure and AI catalysis, the release of the value of data elements and the blossoming of the industry are expected to accelerate in 2026. It suggested focusing on various aspects of the industry chain such as data supply, data transaction circulation, data application development, data services, data security, computational power, and network infrastructure. Guotai Haitong's main points are as follows: 2026 is the "year of releasing the value of data elements". The National Data Work Conference was held in Beijing from December 29th to 30th, 2025. The meeting focused on clarifying the functional positioning of data circulation service agencies, improving the efficiency of data circulation and transaction services, and promoting the prosperity of the data market ecosystem. It explicitly stated that 2026 is the "year of releasing the value of data elements", emphasizing the need to focus on facilitating data flow and resource allocation channels, activating data market supply and demand, prospering the market ecosystem, further promoting data accessibility, flow, effective usage, and security, and promoting the comprehensive integration of data elements into the process of economic value creation to better empower economic and social development. Since 2024, the pace of policy implementation has accelerated, constructing a closed loop system for data elements. In 2020, the Central Committee of the Communist Party of China and the State Council issued the "Opinions on Building a More Perfect Market-oriented Allocation System for Factors", officially listing data as the "fifth factor of production", alongside labor, capital, land, and technology. Guided by top-level design, since 2024, the pace of policy implementation for data elements in China has accelerated, shifting from top-level design documents to practical policy implementation, gradually constructing an institutional closed loop centered around data supply, transaction circulation, scenario development, and infrastructure, laying a solid institutional foundation for the industrialization of data elements. The demand for AI applications is driving a significant supply gap in the data market. According to data from the National Bureau of Statistics, the daily average consumption of Tokens for AI applications in China has surged from 100 billion at the beginning of 2024 to over 30 trillion by the end of June 2025, growing by over 300 times in a year and a half. This rapid growth reflects the expanding scale of AI applications in China, resulting in a significant supply gap in the data market. Investment advice: With the combination of institutional closure and AI catalysis, the release of the value of data elements and the blossoming of the industry are expected to accelerate in 2026. It is recommended to focus on various aspects of the industry chain such as data supply, data transaction circulation, data application development, data services, data security, computational power, and network infrastructure. Risk warning: Risks include policy fluctuations, technology implementation falling short of expectations, and delays in data application development.