证监会相关负责人表示：构建规范、健康的资本市场人工智能生态体系

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].