Core Viewpoint - The article highlights the significant advancements and applications of AI technology in the securities industry, showcased by leading brokerage firms at the 2025 World Artificial Intelligence Conference [2]. Group 1: Citic Securities - Citic Securities launched the first market-level AI system for market value management, named CapitAI-Link, which combines AI algorithms with market value management to provide personalized decision support for listed companies [4]. - The firm is also advancing its AI digital employee system, which aims to enhance efficiency and collaboration in financial services by providing each employee with digital assistants, thereby increasing productivity [4]. Group 2: CICC (China International Capital Corporation) - CICC presented its self-developed digital investment research platform, "CICC Insight," at the conference, emphasizing the role of AI in driving intelligent investment research [6][10]. - The company has supported over 50 companies listed on the Sci-Tech Innovation Board, with a total financing scale exceeding 200 billion yuan, accounting for about 20% of the total IPO financing on the board [9]. Group 3: Citic Jinsheng - Citic Jinsheng released a deep research report titled "AI New Era: Forge Ahead," which discusses the evolution of AI large models and their implications across the industry [11]. - The report outlines the development of AI models and applications, emphasizing the need for a comprehensive understanding of the AI industry from foundational infrastructure to end-user applications [12]. Group 4: Huatai Securities - Huatai Securities focused on investment opportunities in the agent economy during its forum, highlighting the potential of AI agents to operate continuously and interact more rapidly than humans [14]. - The report indicates that the AI chip market for data centers is projected to reach 178.2 billion dollars in 2024, reflecting a 77% year-on-year growth, surpassing the markets for PC and smartphone chips [15].

Core Insights - The article emphasizes the importance of aligning AI digital employees with business needs rather than adopting technology for its own sake, focusing on three dimensions: scenario adaptability, cost control, and growth compatibility [2] Group 1: Identifying Core Needs - Companies must first clarify their core needs, determining whether they require immediate solutions or long-term strategic positioning [2] - Different types of digital employees should be selected based on specific pain points, such as customer service for small e-commerce firms or supply chain data analysis for large manufacturing companies [2] Group 2: Matching Skills to Business Scenarios - The skills required for digital employees vary significantly across different business scenarios, necessitating precise matching to avoid paying for redundant features [3] - Examples illustrate the consequences of selecting inappropriate digital employees, such as increased customer churn due to inadequate response capabilities [3] Group 3: Technical Considerations - Companies should avoid compatibility pitfalls by ensuring that digital employees can seamlessly integrate with existing systems and processes [4] - The complexity of operation should be manageable without requiring full-time IT support [4] Group 4: Cost Assessment - A comprehensive cost analysis should consider both short-term investments and long-term ROI, including direct savings from reduced personnel costs and indirect benefits from improved efficiency [4] - A case study highlights a software company that recouped its investment in a financial digital employee within six months, leading to significant annual net gains [4] Group 5: Trial and Error Strategy - Companies are advised to adopt a "small steps" approach, starting with pilot projects to validate effectiveness before scaling up [5] - It is crucial to check system compatibility and ensure that digital employees can integrate with existing platforms [5] Group 6: Evaluation Standards - Establishing quantifiable acceptance criteria is essential for assessing the performance of digital employees [6] - Companies should monitor the collaboration between human staff and digital employees to ensure that the latter do not increase the workload for human workers [6] Group 7: Measuring Effectiveness - The effectiveness of digital employees should be measurable within three months, focusing on cost reduction, efficiency improvement, and revenue growth [7] - The ultimate goal is for digital employees to act as invisible partners that address current challenges while evolving with business growth [7]