Core Insights - The company has initiated its AI application strategy since 2017, adopting the "AI in All" approach to empower various business lines and systems [1] - With advancements in large model technology, the company has upgraded its AI strategy to "ALL in AI," transitioning from enabling AI to transformative AI [1] - The company has implemented over 150 AI application scenarios across various business areas, creating a new development pattern of "ubiquitous intelligence" [1] Technology Challenges - The company identifies the "hallucination" and interpretability issues of AI as significant challenges, particularly in the finance sector where precision is critical [2] - To address these challenges, the company has developed a "1+N" application system, combining general large models with industry-specific models to ensure reliable service outputs [2] Investment Focus - The company emphasizes the need to focus AI investments on core business areas to generate sustainable business value, especially as the enthusiasm for large model applications wanes [2] - The return on investment will become a central concern for companies, necessitating AI to address industry pain points effectively [2] Industry Development - The company advocates for the establishment of a regulated development order to maintain a healthy industry ecosystem, urging collaboration among regulators, institutions, and clients [2] - Industry associations are working on guidelines to standardize development paths, which will support the healthy growth of AI in the securities sector [2] Future Outlook - The company acknowledges the immense potential of AI while recognizing the challenges, suggesting that a collaborative approach can transform technical challenges into new development opportunities for the securities industry [2]

Core Insights - The 2025 Greater Bay Area Exchange Technology Conference highlighted the transition of AI technology in the securities industry from conceptual exploration to deep implementation, presenting both opportunities for efficiency and challenges for governance [1] - AI is positioned as a core driver for high-quality development in capital markets, with a focus on integrating AI capabilities with market governance needs [1] - The conference emphasized the importance of aligning AI advancements with regulatory frameworks to enhance market development and regulatory enforcement [1] Group 1: AI Technology Development - AI is recognized as a strategic technology leading a new wave of technological revolution and industrial transformation, with the year 2025 being termed the "Year of AI Agents" [2] - The securities industry is becoming a significant application scenario for AI, driving the sector towards greater intelligence, efficiency, and inclusivity [2] - AI's role in the securities industry is more critical than in other sectors, providing substantial support in customer acquisition and revenue generation [2] Group 2: Implementation and Challenges - Companies like Guotai Junan Securities have integrated AI across various business sectors, achieving over 150 AI applications that enhance risk control, investment research, and trading [3] - Regulatory bodies are actively embracing AI to improve oversight and compliance, integrating AI throughout the regulatory process [3] - The financial industry is accelerating its adoption of AI, overcoming challenges such as data governance and computational power limitations [4] Group 3: Future Outlook and Collaboration - AI is expected to enhance the overall competitiveness of the securities industry by improving customer service, operational efficiency, and promoting high-quality development [4] - Challenges such as AI's "hallucination" problem and lack of interpretability pose risks in the finance sector, necessitating careful consideration [4] - The industry is working towards overcoming AI application bottlenecks through technological advancements, regulatory adaptations, and collaborative innovation [5] Group 4: Strategic Initiatives - The Shenzhen Stock Exchange aims to build a world-class digital and intelligent trading platform by focusing on risk prevention, regulatory strength, and high-quality development [6] - Key initiatives include planning intelligent computing infrastructure, implementing cloud applications, and enhancing AI integration in core business areas [6] - The potential of AI in the securities industry is significant, but its development requires guidance from regulatory bodies, practical exploration by institutions, and cooperation from clients [6]