Core Viewpoint - The China Securities Regulatory Commission (CSRC) emphasizes the importance of building a standardized and healthy artificial intelligence (AI) ecosystem in the capital market, aiming to enhance the application level of AI and leverage it as a transformative force for high-quality development in the sector [1][2]. Group 1: AI Application in Capital Markets - The CSRC is closely monitoring the application trends of AI in the capital market, which has shown positive development, characterized by the securities industry leading, followed by funds and futures, with top institutions setting examples [1]. - AI applications have expanded across core areas such as investment research, financing services, investor services, internal control management, information technology, and regulatory oversight [1]. Group 2: Challenges in AI Implementation - Challenges in AI application include non-unified data standards, insufficient high-quality data sources, and issues related to large model "hallucinations," alongside computational supply and cost pressures hindering large-scale and in-depth AI applications [2]. - Regulatory frameworks tailored to the characteristics of AI technology are still maturing, with a need for improved precision and foresight in regulation, as well as enhanced institutional supply [2]. - Traditional risks such as cybersecurity and data security remain significant, with emerging risks like "data poisoning" posing new challenges for risk management capabilities in the industry [2]. Group 3: Strategic Framework for AI Development - The basic work strategy for building a healthy AI ecosystem in the capital market includes promoting innovation while ensuring regulatory compliance, respecting technological evolution, and collaborating across industry ecology, institutional ecology, and regulatory requirements [2][3]. - The industry ecosystem should explore differentiated regulatory frameworks based on the impact and potential risks of AI applications, promote pilot projects, and establish innovation application verification platforms [3]. - The institutional ecosystem must ensure alignment between AI applications and institutional development, adhere to ethical standards, enhance information disclosure, and protect investor rights [3]. Group 4: Compliance and Risk Management - Strict adherence to national and industry regulatory requirements is essential, including establishing content compliance mechanisms and verifying high-risk application scenarios [4]. - Data security management must be strengthened to prevent risks such as data misuse and information leakage, while enhancing network security management to ensure stable operation of AI-related information technology systems [4]. - A collaborative mechanism of "human oversight + model assistance" should be established in critical business areas to mitigate the inherent limitations of AI and prevent risk transmission [4].

Core Viewpoint - The China Securities Regulatory Commission emphasizes the need to build a standardized and healthy artificial intelligence ecosystem in the capital market, balancing innovation promotion and regulatory compliance while focusing on industry ecology, institutional ecology, and strict adherence to regulatory requirements [1][2][3] Group 1: Industry Ecology for AI Development - Establish a differentiated regulatory framework based on the impact and potential risks of AI applications, implementing tiered and classified supervision [1] - Promote pilot projects for "AI + capital market" to quickly develop replicable and scalable practical cases [1] - Set up AI pilot bases and innovation application verification platforms to facilitate the sharing of resources such as computing power, data, and models [1] - Enhance the construction of high-quality data sets in key areas like legal regulations, market information, and disclosure [1] - Strengthen resource support and research to improve incentive measures, talent development, and collaborative innovation among industry, academia, and research [1] Group 2: Institutional Ecology for AI Application - Improve governance structures and strategic planning to align AI applications with institutional development across business, technology, compliance, and risk management [2] - Adhere to national AI ethical guidelines and social norms to ensure compliance with laws, regulations, and ethical standards in AI applications [2] - Enhance information disclosure and investor protection by clearly identifying AI-generated content to safeguard investors' rights [2] - Strengthen data governance by using authoritative data sources and improving data management standards to enhance data quality [2] - Develop risk assessment and emergency response mechanisms to continuously monitor medium to high-risk business scenarios [2] Group 3: Compliance with Regulatory Requirements - Ensure content compliance by establishing content barriers and output verification mechanisms, with high-risk scenarios undergoing manual verification [3] - Mitigate data security risks by enhancing data management to prevent illegal collection, data misuse, information leakage, and other risks [3] - Strengthen cybersecurity management to improve system defense capabilities and ensure the stable operation of AI-related information technology systems [3] - Enhance model management capabilities by creating a comprehensive evaluation system covering safety, compliance, and service capabilities [3] - Recognize the inherent limitations of AI and establish a "human supervision + model assistance" mechanism in critical business areas to prevent risk spillover [3]