On the morning of January 17th, the third session of the 14th Beijing Municipal Committee of the Chinese People's Political Consultative Conference (CPPCC) was successfully concluded after completing all its agenda items. During the meeting, more than 700 municipal CPPCC members, participating units, and specialized committees actively fulfilled their duties by submitting proposals and offering policy advice.

Lin Jing, Chairman and President of Beijing Jiaxun Feihong Electric Co., Ltd. (hereinafter referred to as “Jiaxun Feihong,” stock code: 300213), once again shouldered the important responsibility of a municipal CPPCC member. He brought forward a proposal titled “On Further Unleashing the Potential of Data Elements to Empower High-Quality Development of the AI Industry.” Focusing on hot topics in the technology sector such as the factor market, data resources, and high-quality development of AI, he put forward valuable suggestions.

Committee member Lin Jing noted that AI, as a core track in global technological competition and one of Beijing's dominant industries, has transitioned from data-driven to data-inferential development under the influence of the Scaling Law. This shift has increased the demand for high-quality data. Over the past two years, Beijing has deeply implemented the "Digital Economy Promotion Regulation" and the "Twenty Measures on Data," forming a 20,000 P computing power supply. It has also gathered 40% of the nation's AI enterprises, half of the large models, and a quarter of the funding, creating a significant advantage in the AI sector.

With the development of large models, data has become a key determinant of model performance, necessitating real data from various industries to support breakthroughs in cognitive reasoning. However, China's data element market is still in its early stages of development, facing many bottlenecks that restrict data utilization and development. These are also the issues and obstacles that the AI industry faces in its pursuit of high-quality development:

01 Low Degree of Assetization

Data production and processing involve multiple entities, are replicable, and have complex ownership. The mechanisms for rights confirmation, pricing, and auditing are not clear enough, and many enterprises have not completed the listing of data assets.

02 Low Degree of Openness and Sharing

Enterprise data contains a large amount of business secrets and sensitive information. Some companies, in order to maintain their competitive edge, adopt strict protective measures or even implement "data monopolies." Small and medium-sized enterprises (SMEs) have limited data scale and lack professional talent to conduct related businesses, resulting in fragmented data resources. There are significant security barriers and interest constraints in opening and sharing data.

03 Low Degree of Standardization

There is no unified understanding of data value across industries and enterprises. Inconsistent data collection standards, communication protocols, and data formats during data generation, processing, and circulation lead to varying data quality, increasing the difficulty of integration, circulation, and mutual recognition.

04 Low Level of Market-oriented Transactions

Due to obstacles in rights confirmation, assessment, trustworthy circulation, and profit distribution, it is difficult for data owners, users, and service providers to reach a consensus on profit distribution. As a result, 95% of data transactions are conducted "off-exchange."

In response to these issues, Committee member Lin Jing suggested that as an international science and technology innovation center and an important national data hub, Beijing needs to quickly address these bottlenecks to unleash the potential of data and provide support for the development of large models.

I. Promote Data Asset Listing and Accelerate Data Resource Assetization

• Accelerate the confirmation, certification, and listing of data assets to transform corporate raw data into tradable assets.

• Guide enterprises to establish data management institutions based on their IT departments, conduct data business, and provide operational guidelines and relevant training for data assetization.

• Increase the supply of services for the confirmation, certification, and registration of corporate data assets. Offer rewards and tax incentives for enterprises that complete the listing of data assets. Meanwhile, encourage securities and financial institutions to provide services such as data asset mortgage loans and securitization to unlock data value and promote the optimal allocation of factor markets.

II. Strengthen Industry Data Governance and Unearth Data Resource Value

• Enhance the functions of government data management departments to promote the establishment of industry data standardization management systems. Organize key industries to conduct data resource梳理, compile data asset catalogs, and register data assets. Increase policy and service support for data governance.

• Support and guide leading enterprises to take the lead in building industry databases, improving data circulation and composite application within the industry.

• Encourage SMEs to join vertical industry large model training. Share benefits based on the scale, quality, frequency, and application effectiveness of the data provided. Collaboratively create high-quality AI large model training datasets to address fragmented, non-standardized data resources and the phenomenon of "data silos."

III. Develop Advanced Circulation Technologies and Create a Secure and Trustworthy Data Flow Loop

• Accelerate the implementation of data classification and grading protection mechanisms. Classify corporate data assets according to their importance in accordance with relevant laws, and adopt different protection measures. Implement systems such as network security level protection and critical information infrastructure security protection to enhance the security level of data assets.

• Vigorously promote the application of new technologies such as privacy computing. Support enterprises with conditions to break through key technologies for trustworthy data circulation. Improve the standard certification, technical protection, and operation management systems during data circulation to provide a trustworthy, controllable, and measurable flow environment for the entire data lifecycle.

IV. Persist with Scenario Application Traction and Cultivate a High-Quality Data Trading Market

• Prioritize the application of data in key areas such as finance, healthcare, transportation, government affairs, and intelligent manufacturing to cultivate new products, services, and models based on data elements, achieving value breakthroughs in these fields.

• Rely on platforms such as the Beijing Data Exchange and the Beijing Big Data Center to cultivate a high-quality data element trading market. Promote legislation on ownership certification mechanisms, price formation mechanisms, benefit distribution mechanisms, and dispute resolution mechanisms. Guide market entities to orderly open data, use data in compliance, and jointly explore the commercial value of data.

Background and Conclusion

Mission-Bearing, People-Oriented, Collective Wisdom, and Fulfilling Duties for the People: In 2024, the Standing Committee of the Beijing Municipal Committee of the Chinese People's Political Consultative Conference (CPPCC) advanced proposal work to the highest standard. A total of 93% of the proposals and suggestions were adopted or partially adopted, accounting for the total number of proposals handled throughout the year. This demonstrated the unique advantages of socialist consultative democracy in promoting the development of the capital in the new era.

Committee Member Lin Jing: As a representative of the science and technology community and a three-term member of the Beijing Municipal Committee of the CPPCC, Committee Member Lin Jing has repeatedly focused on key industrial terms and buzzwords such as artificial intelligence and new-quality productive forces. Committed to meeting the demands of the times, he actively offers valuable suggestions for the capital's scientific and technological innovation and development. He will also make new and greater contributions to writing a Beijing chapter of Chinese modernization.