证券日报网1月9日讯 ，楚天龙在接受调研者提问时表示，楚天龙积极响应国家关于深入实施"人工智能 +"行动号召，深度融合大模型、AI数字人、知识图谱等先进技术，构建起"硬件-软件-服务"于一体的完 善产品体系，涵盖AI咨询问答数字人、场景智能体、AI数字员工等多元形态，并成功中标2025年重庆 社银合作智能化场景建设项目（一期），该项目以"智能化、一体化、便民化"为核心目标，涵盖社银合 作服务大厅建设、场景智能体建设、AI底座资源及服务、运维服务四大模块，具体包括AI社银服务一 体机、数字人交互终端、社保卡便携式发卡机等智能硬件，以及风控规则助手、工伤服务咨询导办助手 等对内对外智能体，为政府、银行、运营商等行业客户提供全场景数智解决方案。截至2025年底，公司 已在多地打造标杆案例，助力万千企业与群众享受到高效智能的服务。 （文章来源：证券日报） ...

证券代码：003040 证券简称：楚天龙 问题 2、目前公司 AI 业务有没有新增示范类项目落地？ 交流回复： 楚天龙股份有限公司投资者关系活动记录表 编号：【2026】0108 在持续巩固现有业务基础的同时，楚天龙紧跟政策导向，聚焦跨 境支付场景生态建设及运营服务等方向。公司依托区块链、智能合约 等关键技术积累，积极探索并推动数字货币桥应用场景、跨境结算优 化等项目落地，通过一个个具体的、高价值的场景来落地我国金融科 技创新战略，实现楚天龙商业成功与社会价值。 楚天龙积极响应国家关于深入实施"人工智能+"行动号召，深度 融合大模型、AI 数字人、知识图谱等先进技术，构建起 "硬件 - 软 件 - 服务" 于一体的完善产品体系，涵盖 AI 咨询问答数字人、场景 智能体、AI 数字员工等多元形态，并成功中标 2025 年重庆社银合作 智能化场景建设项目（一期），该项目以 "智能化、一体化、便民化" 为核心目标，涵盖社银合作服务大厅建设、场景智能体建设、AI 底 座资源及服务、运维服务四大模块，具体包括 AI 社银服务一体机、 数字人交互终端、社保卡便携式发卡机等智能硬件，以及风控规则助 手、工伤服务咨询导办助手 ...

编者按2025年是"十四五"规划收官之年，也是"十五五"规划谋篇布局之年。这一年，我国石油和化工行 业认真贯彻中央经济工作会议精神，进一步落实全国新型工业化推进大会部署要求，锚定实现新型工业 化的关键任务，进一步推动信息化和工业化深度融合。行业人工智能（AI）大模型、工业互联网等信 息技术的应用不断深入，助推我国工业经济向新向优发展。《智能制造周刊》特遴选行业智能制造领域 2025年度十大新闻，以飨读者。 石化行业首位AI数字员工"上岗" 1月18日，中国石化在北京举行数字员工发布仪式，正式推出首位AI数字员工，并在广西南宁新阳加油 站等全国40余座加能站同步试点"上岗"。这是我国石油石化行业首位AI数字员工。 该数字员工由科大讯飞星火大模型提供算法和算力支持，融入自助加油、App智能导航及客户服务系 统，可以记录和分析消费偏好，全天候在自助加油、易捷加油APP及电话客服提供实时交互服务，为客 户解答疑问、指导自助加油操作、推荐个性化营销活动，精准高效解决客户诉求，显著提高了服务效 率。 目前，该数字员工已覆盖中国石化31个省市的加能站点。据介绍，中国石化也正在以"新一代人工智能 加油站成套技术"项目为依托， ...

中经记者 曲忠芳 北京报道 记者了解到，就在2025年11月11日时，真爱美家公告称收到了探迹的收购要约，后者拟通过"协议转让 +部分要约收购"的方式收购真爱美爱，总花费金额约18亿元。探迹方面专门为此笔交易设立了"特殊目 的载体（SPV）"——探迹远擎，即广州探迹远擎科技合伙企业（有限合伙）作为操作主体。待交易顺 利落地后，探迹远擎将合计持有真爱美家44.99%的股权及对应表决权，成为新任控股股东，上市公司 实际控制人将变更为探迹科技创始人兼CEO黎展。 不难看出，探迹科技此番将品牌标识与真爱美家股票代码一起实现"太空首秀"显然是为这起跨界并购案 进一步造势。 黎展公开表示："航天探索是人类千年梦想的延续，探迹的品牌名随卫星进入太空，意味着技术无边 界、发展无止境，未来的竞争必将升级至以数据驱动决策、以智能定义价值的新阶段。" （编辑：张靖超 审核：李正豪 校对：翟军） 探迹科技创立于2016年，核心产品包括企业级大模型智能体开发平台"太擎"和数据云底座"旷湖"，为 B2B、B2C企业提供旨在提高经营效率的"AI数字员工"，同时还有销售智能体Futern，帮助外贸企业拓 展海外市场。截至目前，探迹科技服务的 ...

Core Viewpoint - A profound transformation in corporate structure is occurring in Silicon Valley, where AI agents are evolving from mere tools to autonomous colleagues, significantly impacting the real estate industry [1][3]. Group 1: AI Transformation in Real Estate - The real estate industry, characterized by high capital intensity and long decision chains, is becoming a breakthrough point for AI applications, with digital employees capable of performing tasks traditionally requiring multiple human roles [3][11]. - Deep Intelligence's "Kerry Digital Employee" has been recognized for its real industry value and scalable application capabilities, winning the "2025 Outstanding AI Product Award" [4]. - The introduction of digital employee teams, such as the "Gold Medal Case Field" team, showcases a collaborative approach to cover the entire process from market analysis to customer service in new housing projects [7][8]. Group 2: Cost Efficiency and Organizational Change - Traditional real estate marketing teams typically require 6-8 personnel with a monthly cost exceeding 150,000 yuan, while digital employees can cover the same functions for around 2,500 yuan, reducing labor costs by over 90% [11]. - The shift towards AI-native organizations emphasizes a model where human experts focus on high-value tasks while digital employees handle standardized, time-consuming tasks, creating a synergistic collaboration [11]. Group 3: Unique Industry Advantages - Deep Intelligence's AI solutions are tailored to the real estate sector, integrating industry knowledge, business processes, and proprietary data to create a specialized AI space that overcomes traditional barriers to high-end capabilities [13][16]. - The company has established four unique advantages: a vast structured database, a knowledge graph from unstructured documents, expert thinking encoding, and a stable multi-agent architecture for collaborative tasks [16]. Group 4: Broader Implications and Future Outlook - The trend of integrating digital employees is not limited to real estate; leading companies across various sectors are adopting similar strategies, with the AI digital human market in China projected to reach 4.12 billion yuan in 2024, growing by 85.3% [19]. - The future competitiveness of enterprises will depend on their ability to leverage top-tier professional capabilities through AI in a cost-effective and sustainable manner [20]. - The introduction of digital employees in real estate represents a significant opportunity for companies to break through the barriers of high-end capability scarcity, positioning them for success in the evolving market landscape [21].

首先，银行实体网点收缩是中小银行改革化险的主动选择。近年来，部分村镇银行、农商行风险逐渐暴 露，内控缺失、公司治理薄弱、区域经营受限等问题突出。监管部门自上而下推动合并重组，加速了高 风险机构的市场化退出。截至12月初，年内因合并或解散注销的银行已超370家，其中近六成为村镇银 行。内蒙古、四川、吉林等地通过组建省级农商行、推进市级统一法人改革，整合区域内农信机构，实 现规模效应与风险化解。这一过程虽然在一定程度上造成了网点的裁撤，但也是行业挤水分、提质量的 必经阶段。 证券时报记者谢忠翔 今年以来，银行网点"关停潮"引发市场广泛关注。 据证券时报记者统计，截至发稿前，年内已有超9900家银行网点终止营业。其中，农商行网点占比超 55%，农村信用社网点和村镇银行网点占比分别为20%、9%。这一趋势背后，不仅是金融科技深化带来 的渠道重构，更是中小银行尤其是农村金融机构在改革化险与数字化转型双重施压下的真实写照。 其次，金融科技的深度渗透从根本上改变了银行业的服务生态。当前，手机银行渗透率已接近90%，超 八成个人业务可在线完成。从智能柜台、远程云柜，到AI数字员工、大模型赋能风控与营销，技术替 代人工已成为不 ...

今年以来，浙江加快推进人工智能赋能新型工业化，传统工厂智能化升级的需求迫切，催生全新的服务市场。今 天的《三张订单看变化》，来看一张传统热电厂的AI新订单。 在海盐恒洋热电，与设备打了十几年交道的老师傅李忠华，正在训练一名"新手"——锅炉供热系统的"AI数字员 工"，"它"已经能根据用户需求自动调节供气。 这名"AI数字员工"由恒洋热电和宁波的蓝卓数字科技共同研发，预计每年可以节省200万元左右的成本。这吸引了 体量远大于恒洋热电的合肥热电厂，签下了一张数字服务订单。 浙江恒洋热电有限公司技术部经理 李忠华：我们之前是跟人要讲清楚，做一些培训，像一些原理、操作方法、异 常处理，但是现在，我们要把这些跟人讲的东西要跟AI去讲清楚。 浙江恒洋热电有限公司总经理 顾建平：合肥热电当时是到处考察，他们来了以后觉得一个企业能这么快把AI装入 到这个系统里面，他们感觉到很惊讶。 亲眼看到AI技术带来的效益，合肥热电厂很快下单，让恒洋热电有了主业之外的第一张AI数字服务订单，从此在 传统业务之外开辟了数字服务的新赛道。 蓝卓数字科技有限公司嘉兴区域经理 殷秀敏：合肥的这些热电厂跟它（恒洋）的同行，就是业务类型是相似的， 那 ...

格隆汇新股 市值30亿，珠海冲出一家AI数字员工IPO，高瓴、温氏股份押注 原创 阅读全文 ...

Core Insights - The report highlights Jinan's rise to the fifth position in the Urban Comprehensive Development Index 2025, attributing this success to its focus on artificial intelligence as a key driver for urban transformation [1] - Jinan's "AI Spring City" initiative aims to integrate AI across various sectors, including industry, agriculture, services, and digital governance [1] Group 1: AI Integration in Urban Development - Jinan is implementing the "AI Spring City" initiative, focusing on AI applications in industrial, agricultural, and service sectors [1] - The city emphasizes the importance of practical applications of AI technology in urban operations and industry development [1][2] - The integration of AI in public services, such as heating management, is a priority, with the goal of enhancing efficiency and user experience [2][3] Group 2: Technological Advancements and Data Utilization - The DeepSeek model has successfully handled 120,000 calls during the heating season, demonstrating AI's capability to manage high volumes of inquiries efficiently [3] - The AI model has been designed to understand both technical and layman's terms, improving communication with the public [3] - Jinan's public data resources have been consolidated, with over 15 billion data entries available to enhance city services [5] Group 3: Economic Impact and Growth - The AI core industry in Jinan is projected to reach 48.2 billion yuan in 2024, marking a 25.2% year-on-year growth [7] - The city has established a comprehensive ecosystem for AI development, including hardware, software, algorithms, and applications [7] - The revenue from AI and smart city initiatives for ShenSi Electronics reached 142 million yuan in the first half of 2025, reflecting a 414.01% increase year-on-year [7]

Core Insights - The article discusses the cyclical nature of AI investment, highlighting a pattern where enthusiasm peaks at the beginning of the year but wanes by year-end due to a lack of tangible returns [1][3] - It emphasizes that AI is not merely a short-term bubble or a tool exclusive to large companies, but rather a technology that requires a strategic approach to integrate with business operations for effective implementation [3][4] Group 1: AI Investment Trends - Many companies experience a cycle of initial excitement followed by project stagnation due to unmet expectations and a disconnect between technology and business needs [1][2] - A significant number of enterprises abandon AI initiatives midway, with only about 300 out of thousands achieving real results [2] Group 2: Identifying Opportunities and Pitfalls - Companies that successfully leverage AI focus on the "middle ground" of integrating AI with their specific business needs, avoiding the extremes of macro-level concepts and micro-level techniques [3][4] - Common pitfalls include investing in flashy AI projects without addressing real business problems, leading to low usage rates and increased customer complaints [5][6] Group 3: Effective AI Implementation Strategies - Successful AI applications often target high-frequency, repetitive tasks, yielding quick returns on investment and building confidence in AI's value [7][12] - Companies that integrate AI into their core products or services can create new revenue streams and enhance operational efficiency [15][16] Group 4: The Five-Level Implementation Framework - The article introduces a "L1-L5" framework for AI implementation, which helps businesses systematically approach AI integration based on their specific industry needs [9][11] - Levels L1 and L2 focus on validating AI's value with minimal investment and optimizing core processes, while levels L3 to L5 emphasize transforming AI into a revenue-generating engine and building industry-wide ecosystems [14][18] Group 5: Recommendations for Different Business Sizes - Small and medium-sized enterprises are advised to start with low-cost, high-impact AI applications to achieve quick wins [21] - Mature companies should focus on breaking down data silos and embedding AI into their core operations to gain a competitive edge [22] - Leading firms are encouraged to develop AI-native products and build ecosystems to capitalize on long-term market opportunities [23]