在8月5日举行的百度AI Day开放日上，百度智能云宣布推出首批AI数字员工，涵盖营销经理、还款助理、汽车销 售、促销专员、产品经理、课程顾问、招聘专员等核心业务职能。 "大模型的能力正以前所未有的速度迭代与进化、能力边界也在不断拓展；大模型厂商以多模态大模型能力为基 础，开始推出世界模型，构建了物理世界动态建模、因果推理与反事实推演、长期预测与规划等独特能力。"百度 副总裁阮瑜表示，大模型的飞速进化，推动AI从人机协同的Copilot（AI助手）形态，向具备自主执行能力的Agent （智能体）形态跃迁，并进一步向AI主导的Agentic（代理型人工智能）方向深化。 在石峥看来，传统Agent工具常囿于机械应答、流程僵化、跨平台数据割裂等瓶颈，难以创造真正的业务闭环价 值。而数字员工作为超越传统Agent的新型生产力，能够精准满足各行业场景的专业化、个性化需求，不仅懂业 务、会思考，还能直接植入具体业务流程，对结果负责。 当工作"搭子"变成AI数字人，会发生什么？ 阮瑜进一步表示，在Agentic时代，日常工作中会出现越来越多的新型"劳动者"，智能体将会以"数字员工"的形态参 与到企业运行的各个环节当中，而数 ...

Core Viewpoint - Baidu Smart Cloud has launched the world's first AI digital employees, marking a significant breakthrough in enterprise-level services through the integration of AI technology [1][3]. Group 1: AI Digital Employees - The AI digital employees cover various core business roles such as marketing managers, repayment assistants, automotive sales, promotional specialists, product managers, course consultants, and recruitment specialists [1]. - These digital employees leverage Baidu Smart Cloud's comprehensive AI capabilities, combining large models, digital human technology, and industry expertise to achieve an efficient work state right out of the box [3]. Group 2: Market Potential - The demand for AI marketing in enterprises has seen explosive growth, with the Chinese AI Agent marketing and sales market expected to reach approximately 44.2 billion yuan in 2024, aiming for a trillion-level market space in the next five years [4]. - The marketing sector is identified as the optimal scenario for the implementation of AI Agents due to its high-frequency user interactions and complex business environments [4]. Group 3: Advantages of Digital Employees - Traditional Agent tools often face limitations such as mechanical responses and fragmented data across platforms, while digital employees can meet specialized and personalized needs across various industries [6]. - In the recruitment sector, digital employees can efficiently handle the entire process from outreach to interview scheduling, resulting in a 40% increase in interview attendance rates [6]. - In the education sector, digital employees manage the entire process from enrollment inquiries to renewal conversions, also improving employee efficiency by 40% [6]. Group 4: Technological Innovations - Baidu Smart Cloud has developed a cross-modal voice language model based on Cross-attention technology for real human-like interaction and utilized 4D scanning technology for high-precision imaging [7]. - The digital employees are trained on over 100 vertical industry standard operating procedures (SOPs) using more than 100,000 hours of industry practical data [7]. - The company is focused on expanding digital employee applications in the education, automotive, finance, and fast-moving consumer goods sectors, with low entry costs for businesses [7].

数字员工"懂业务、给结果、可进化"的强大效能，植根于百度智能云AI全栈能力的深厚积淀。数字员工 的核心技术壁垒在于"智能化大脑""真人级形象""行业化内核""进化型基因"四大升级，正加速推动AI从 工具进化为业务伙伴。 目前，百度智能云正持续打造更多岗位的数字员工，深度赋能企业营销获客与客户服务。今年百度智能 云将重点拓展教育、汽车、金融、快消四大行业的数字员工场景，联合头部客户打造高校招生顾问、 4S店销售专员、银行营销专员等典型样板，企业使用门槛低至万元级，为更多行业提供低门槛、高适 配的智能化解决方案，助力企业快速拥抱智能化变革。 石峥分享，当下企业真正需要的是能扛KPI、对业务结果负责的Agent。百度智能云深度融合客悦智能 客服十年的对话能力积累与曦灵数字人七年的技术沉淀；基于大模型的Agent架构不仅实现端到端的智 能交互、更能驱动持续的业务优化和结果生成，打造出国内首批AI数字员工，实现了从功能执行到业 务决策、成果交付的质变。 目前，百度智能云数字员工已率先应用于百度客服中心的在线分流沟通和智能服务回访。数据显示，数 字员工实现7x24小时高效处理客户咨询，用户申保成功率提升60%、服务时效提 ...

中国经济网北京8月5日讯（记者 李方）当AI开始主动洞察需求、解决问题，成为独立的业务执行者， 新一代数字员工应运而生。8月5日，百度AI Day开放日现场，百度智能云宣布推出全球首批AI数字员 工，涵盖营销经理、还款助理、汽车销售、促销专员、产品经理、课程顾问、招聘专员核心业务职能。 据悉，AI数字员工依托百度智能云领先的AI全栈能力，深度融合了大模型、数字人技术及行业Know- How三大业务优势，能够实现开箱即用，上岗即胜任，精准赋能垂直业务场景的同时持续沉淀岗位能 力，以"懂业务、给结果、可进化"三大特性重新定义企业级智能服务能力，真正成为企业可信赖的数字 业务伙伴。 目前，百度智能云数字员工已率先应用于百度客服中心的在线分流沟通和智能服务回访。数据显示，数 字员工实现7x24小时高效处理客户咨询，用户申保成功率提升60%、服务时效提升18h。谈及行业未来 发展，石峥认为，人机协同是现阶段主流趋势，未来或将实现多数字员工协同解决复杂任务。 百度副总裁阮瑜在开放日现场分享，大模型的能力正以前所未有的速度迭代与进化、能力边界也在不断 拓展；大模型厂商以多模态大模型能力为基础，开始推出世界模型，构建了物理世 ...

Core Insights - Major securities firms showcased their AI advancements at the 2025 World Artificial Intelligence Conference, highlighting the integration of AI technology into various business scenarios within the securities industry [1] Group 1: Citic Securities - Citic Securities launched the industry's first AI-driven market value management system, CapitAI-Link, which combines AI algorithms with market value management to provide personalized decision support for listed companies [2] - The firm is also advancing its AI digital employee system, aiming to enhance efficiency and collaboration in financial services by providing each employee with multiple digital assistants [2] 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 the transformation of the financial sector [3] - The company has supported over 50 companies listed on the Sci-Tech Innovation Board, with a total financing amount exceeding 200 billion yuan, accounting for about 20% of the board's IPO financing [3][4] Group 3: CITIC Construction Investment - CITIC Construction Investment released a deep research report on AI and industry development, indicating that AI models are evolving towards greater efficiency and reliability [5][6] - The report covers the entire AI industry chain, from foundational computing infrastructure to application scenarios, aiming to identify investment opportunities across hardware and software [6] Group 4: Huatai Securities - Huatai Securities focused on investment opportunities in the agent economy during its forum, noting that AI agents can operate 24/7 and interact faster than humans [7] - The firm highlighted that the AI chip market for data centers is projected to reach 178.2 billion USD in 2024, with a year-on-year growth of 77%, surpassing the PC and smartphone chip markets [7] - It is suggested to monitor investment opportunities in the server supply chain, as well as addressing infrastructure bottlenecks that currently limit AI development [8]

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]