Investment Rating - The report does not explicitly state an investment rating for the industry. Core Insights - The equipment manufacturing supply chain is transitioning from digitalization to intelligent decision-making, marking a critical phase of smart transformation [7][11]. - The complexity of global supply chains necessitates the adoption of AI technologies for real-time collaboration and intelligent decision-making [8]. - Current digital systems have reached efficiency bottlenecks, highlighting the need for enhanced cross-enterprise collaboration and data integration [12]. Summary by Sections 1. Transition from Digitalization to Intelligent Decision-Making - The equipment manufacturing industry, particularly automotive, is undergoing structural adjustments due to de-globalization, leading to complex supply chain networks involving thousands of suppliers [7]. - Intelligent decision-making is essential to address the challenges posed by global complexity, technological integration, and intensified market competition [8]. - Existing digital systems like ERP and WMS are primarily internal, failing to achieve deep interconnectivity and collaboration across enterprises, resulting in significant efficiency challenges [12]. 2. Intelligent Agents as Key to Supply Chain Collaboration - Generative AI-driven intelligent agents are emerging as solutions to the management challenges faced in complex supply chains, transitioning from algorithmic tools to business assistants [22]. - Intelligent agents can process vast amounts of unstructured data, ensuring real-time and accurate decision support for manufacturers [24]. - They help reduce supplier management difficulties and control procurement costs by analyzing supplier quotes and identifying potential premium areas [26]. 3. Characteristics of Intelligent Agent Technology Vendors - The intelligent agent market consists of four main types of technology vendors: foundational model vendors, industrial software vendors, data intelligence vendors, and AI-native application vendors [31]. - Each vendor type has unique strengths and weaknesses, with foundational model vendors excelling in model capabilities but lacking industry-specific knowledge [31]. 4. Case Study: Yixun Technology - Yixun Technology has developed a Data Agent platform, Alaya, which focuses on data-driven decision-making in the automotive manufacturing sector [35]. - The platform addresses data silos and enhances procurement efficiency, achieving over 60% improvement in procurement processes for a German automotive company [46]. - Yixun's competitive advantage lies in its robust data processing capabilities and deep industry know-how in automotive supply chains [42]. 5. Future Outlook for Intelligent Agents in Equipment Manufacturing - Intelligent agents are evolving from single-point tools to collaborative digital employee clusters, enhancing overall supply chain efficiency [49]. - The progression of intelligent agents will lead to greater autonomy in decision-making, enabling them to perform complex tasks independently [50]. - Future developments will see multiple intelligent agents working together across various supply chain functions, creating a more resilient and agile manufacturing ecosystem [56].

Core Viewpoint - The capital market is witnessing a convergence of AI and industrial upgrades, with Beijing Defeng New Journey Technology Co., Ltd. (Defeng New Journey) applying for an IPO in Hong Kong, highlighting the dual nature of investment logic in the AIoT sector, which relies on long-term technological accumulation and client relationships rather than rapid growth [1] Group 1: Company Overview - Defeng New Journey focuses on AI-enabled industrial IoT production optimization software solutions and has served over 200 state-owned enterprises, delivering more than 600 projects [1] - The company reported cumulative revenue exceeding 1.24 billion yuan from 2023 to September 2025, but also accumulated losses of nearly 640 million yuan [1] - The growth trajectory is characterized by steady revenue increase, with revenue projected to grow from 313 million yuan in 2022 to 525 million yuan in 2024, reflecting a compound annual growth rate of over 29% [2] Group 2: Financial Performance - Despite revenue growth, Defeng New Journey has not achieved profitability, with net losses continuing from 2022 to 2024, totaling 700 million yuan over three years [2] - The gross margin improved from approximately 22% in 2022 to about 26% in the first half of 2025, indicating the emergence of scale effects [2] - The company's revenue structure heavily relies on AIoT solutions, which contributed approximately 93.9% of revenue in the first half of 2025, highlighting the challenges of high R&D and market development costs [3] Group 3: Industry Context - The AIoT market in China is projected to grow from approximately 54.1 billion yuan in 2020 to about 111.9 billion yuan in 2024, with expectations to reach around 220.9 billion yuan by 2029 [4] - Defeng New Journey ranks fifth among independent AIoT service providers in China, with a market share of about 1.8%, and third in the energy sector with a market share of approximately 9.9% [4] - The industry is characterized by high fragmentation and intense competition, with no clear market leader, posing challenges for Defeng New Journey against established competitors [4] Group 4: Business Model and Challenges - The company faces a dilemma between scale economy and customization, as industrial AIoT solutions require tailored development, leading to high delivery costs and long project cycles [7] - Transitioning from a project-based revenue model to a subscription-based model is essential for improving financial health, but this depends on changes in customer purchasing habits and product standardization [8] - Key factors for potential value reassessment post-IPO include effective cash flow management, the ability to lower delivery costs through platform modularization, and successful market expansion beyond the energy sector [8]

Summary of Key Points from the Conference Call Industry Overview - The document discusses the evolution of internet entry points from portals to search engines and now to AI search, indicating a significant shift in how users access information. Traditional SEO is experiencing diminishing returns, while Generative Understanding (GU) is emerging as a new marketing paradigm [1][3][4]. Core Insights and Arguments - **AI Search and GU Market Potential**: The global GU market is expected to capture 10%-20% of the ICU budget, potentially reaching a market size of tens of billions of dollars. Traditional search engine traffic is projected to decline, with AI-native search gaining market share [1][6]. - **Growth in China**: The Chinese GU market is forecasted to grow rapidly, reaching 5.24 billion yuan by 2030, indicating a nearly ninefold increase over five years [1][8]. - **Business Model Transition**: The GU business model is shifting from project-based to a subscription-based SaaS and PaaS hybrid model, with a clear path demonstrated by overseas benchmark companies [1][9]. - **High Technical Barriers**: GU technology has a higher technical threshold compared to traditional SEO, with a concentration rate of around 60% in the industry, aligning with trends in the computer software sector [1][10]. Important but Overlooked Content - **RAG Architecture**: The RAG architecture involves five key steps: knowledge base construction, vectorization and indexing, retrieval and ranking, context enhancement and generation, and dynamic updates. This framework enhances semantic relevance and authority, forming a trust engineering model [1][5]. - **Market Dynamics**: By 2028, traditional search engine traffic is expected to decline by 25%, with 80% of that traffic shifting to AI dialogue platforms. AI-native search is projected to account for 45% of the global search market by 2028 [6]. - **Company Initiatives**: Companies like MaiFudi and MingYue Technology are actively developing GU capabilities, launching products like GEO Intelligent Body, which have shown promising market feedback [2][11][12]. Company-Specific Developments - **MaiFudi**: Launched GU business in early 2025, with the GEO Intelligent Body generating 9 million yuan in revenue in December 2025, with an annualized revenue potential of 100 to 200 million yuan [11]. - **MingYue Technology**: Focused on GU since 2024, offering a comprehensive solution that includes user intent acquisition, content generation, and distribution [13]. - **Fourth Paradigm**: Their GEO solution includes strategy design, knowledge engineering, effect evaluation, and ecosystem collaboration, aimed at enhancing brand visibility in AI responses [15][16]. Future Trends in Marketing Technology - The marketing technology sector is expected to grow significantly, with a projected compound annual growth rate of nearly 30% over the next five years. Companies that adapt to new technologies will likely capture larger market shares [17]. - AI applications are anticipated to enhance digital transformation in enterprises, benefiting companies with industry-specific knowledge and comprehensive solutions [18][19]. This summary encapsulates the key points from the conference call, highlighting the evolution of GU, market potential, company initiatives, and future trends in the marketing technology landscape.

Investment Rating - The report maintains a "Recommended" investment rating for the computer industry [2][6]. Core Insights - The AI medical sector is experiencing rapid development, with significant commercial opportunities emerging. Major players like NVIDIA and Eli Lilly are investing heavily in AI drug development, while domestic companies like Ant Group are promoting AI health management products [5][13][14]. - Alibaba's Qianwen app has transitioned into the "AI service era," integrating over 400 AI service functions and achieving over 100 million monthly active users, indicating strong user engagement and ecosystem integration [15][17]. - The report highlights the importance of AI infrastructure development in China, emphasizing the need for a self-sufficient and efficient computing foundation to support the growing demand for AI applications [16]. Summary by Sections AI Empowerment in Healthcare - The report notes that AI is reaching a commercialization inflection point in healthcare, with significant investments and partnerships forming to accelerate AI drug development and health management solutions [5][13][14]. - Key areas of growth include AI drug development, AI-assisted medical imaging, and personal health management, which are expected to see increased investment and demand [14]. Development of AI Ecosystem - Domestic tech giants are leveraging their vast user bases and data resources to build comprehensive AI ecosystems, enhancing user experience and operational efficiency [15][16]. - The integration of AI services within existing platforms is seen as a critical factor for rapid deployment and market penetration [15]. Investment Recommendations - The report suggests focusing on AI computing companies such as Cambricon (688256.SH), Haiguang Information (688041.SH), Inspur Information (000977.SZ), and Zhongke Shuguang (603019.SH) [6][17]. - It also recommends monitoring vertical AI application companies like Kingsoft Office (688111.SH), Dingjie Zhizhi (300378.SZ), and Han's Information (300170.SZ) for potential investment opportunities [6][17].

Core Viewpoint - The company, Saiyi Information, experienced a decline in stock price and trading volume, indicating potential liquidity issues and a decrease in investor confidence [1][2]. Group 1: Stock Performance - On January 16, Saiyi Information's stock fell by 3.57%, with a trading volume of 643 million yuan [1]. - The net financing buy on that day was -43.26 million yuan, indicating more selling than buying [1]. - The total financing and securities lending balance as of January 16 was 498 million yuan, with financing balance at 497 million yuan, accounting for 4.51% of the circulating market value [1]. Group 2: Financial Performance - For the period from January to September 2025, Saiyi Information reported a revenue of 1.501 billion yuan, a year-on-year decrease of 11.96% [2]. - The net profit attributable to shareholders was 27.6147 million yuan, down 70.83% year-on-year [2]. - Cumulative cash dividends since the company's A-share listing amounted to 262 million yuan, with 124 million yuan distributed over the past three years [2]. Group 3: Shareholder Information - As of September 30, 2025, the number of shareholders increased to 39,000, a rise of 6.40% from the previous period [2]. - The average number of circulating shares per shareholder decreased by 6.52% to 8,448 shares [2]. - Among the top ten circulating shareholders, Huazhang Small and Medium-sized Growth Mixed Fund held 4.3112 million shares, an increase of 982,400 shares compared to the previous period [2].

Investment Rating - The report assigns an "Accumulate" rating for the industry [4][33]. Core Insights - The report emphasizes the integration of AI and industrial manufacturing, highlighting the transition from "perceptual interconnection" to "deep intelligence" through policies that promote the development of industrial internet platforms [2][21]. - It outlines four major innovative actions proposed by the policy: platform cultivation, data intelligence enhancement, large-scale application, and ecological support, focusing on the deep integration of AI and industrial internet [2][10]. Summary by Sections 1. Policy Overview and Key Indicators - The report discusses the "Action Plan for Promoting High-Quality Development of Industrial Internet Platforms (2026-2028)" issued by the Ministry of Industry and Information Technology, defining industrial internet platforms as crucial for data aggregation, model accumulation, and application development [8]. - By 2028, the plan aims for over 450 influential platforms, more than 120 million industrial device connections, and a platform penetration rate exceeding 55% [9]. 2. Four Major Action Frameworks 2.1. Platform Cultivation - The report advocates for differentiated platform development, focusing on professional, industry-specific, and collaborative platforms to enhance digital product and service supply [10][12]. - It promotes a "small, fast, light, and precise" approach to digital solutions, transitioning from project-based to subscription-based models [10]. 2.2. Data Intelligence Enhancement - The report highlights the need to improve data collection and integration capabilities, establishing a robust industrial data labeling system and exploring new data management models [13][14]. - It encourages the development of a high-quality industrial model system and supports the "Model as a Service" (MaaS) approach [14][15]. 2.3. Large-Scale Application - The report emphasizes the importance of applying digital management and intelligent production models in traditional industrial settings, particularly for small and medium-sized enterprises [16][17]. 2.4. Ecological Support - The report calls for the establishment of an open-source community for industrial internet platforms and the development of a new standard system to enhance security and data management [19][20]. 3. AI + Manufacturing - The report outlines the synergy between various policies aimed at integrating AI into manufacturing, with specific targets for the development of industrial intelligent entities and high-quality data sets by 2028 [21][22]. - It notes a rapid increase in the penetration rate of industrial intelligent entities, indicating a shift from experimental phases to widespread application across multiple scenarios [22]. 4. Investment Recommendations - The report recommends focusing on companies such as Zhongkong Technology, Rilian Technology, and others, while suggesting to pay attention to companies like Weihong Co. and Rongzhi Rixin [23].

Summary of Key Points from the Conference Call Industry Overview - The focus on AI applications is expected to be a key direction for industries in the future, with related business projected to maintain significant growth, potentially doubling by 2026, contributing approximately 10% to total revenue [2][5] - The AI innovation is anticipated to significantly expand market demand, with estimates suggesting a tenfold increase, particularly in the labor service market, with potential market sizes of around $10 trillion in the U.S. and approximately 10 trillion RMB in China [2][6] Core Insights and Arguments - The transition from hardware infrastructure investment to software and application investment typically follows a three-year cycle, as seen in previous tech revolutions like the internet and cloud computing. The current AI wave is expected to follow a similar trajectory [3] - AI applications are seen as crucial for value creation, as substantial capital investments in infrastructure need to be translated into practical applications across various industries [3] - Key factors for selecting AI application targets include high-quality vertical data, industry know-how, customer scenarios, and model capabilities, which collectively determine a company's ability to thrive in the AI wave [7] Specific Areas of Interest - Notable areas for investment include productivity tools (e.g., programming tools, multimodal generation tools) and marketing tools (e.g., generative user experience, sales agents, and customer service agents), which are showing rapid implementation trends [2][8] - Potential core applications and segments for 2026 include large marketing concepts (programmatic advertising, sales agents, customer service), general ERP scenarios, AI in healthcare, and physical AI [4][9][10] Investment Recommendations - In the A-share market, recommended companies include Tax Friend Co., Focus Technology, Guoneng Rixin, Dingjie Software, and Saiyi Information, among others [11] - In the Hong Kong market, companies like Kingdee International, Fubon Group, and Mingyuan Cloud are highlighted for their competitive strength and growth potential [12] AI in Healthcare - The healthcare AI sector is rapidly advancing, with significant developments in both domestic and international markets. For instance, Ant Group's AI product has reached nearly 30 million monthly active users, and collaborations with major pharmaceutical companies are yielding substantial orders [13][14] - AI in drug development is enhancing research capabilities and expanding into various industries, with companies like Jindeng Holdings achieving significant growth through partnerships [14] AI in Industrial Applications - AI applications in industrial settings are supported by clear policy guidelines, emphasizing the need for continuous refinement of general models to specific industry applications. Companies in industrial software are expected to see growth in orders related to AI business [23] - Industrial software firms can leverage AI for internal process optimization, enhancing overall operational efficiency [24] AI in Financial Services - The AI finance sector has shown a clear development path, with significant breakthroughs and market enthusiasm. Companies like Deepseek and Upstart are leading the charge, and the digital RMB initiative is creating new opportunities in payment and settlement ecosystems [27] Conclusion - The ongoing advancements in AI technology and its applications across various sectors present substantial investment opportunities. Companies that can effectively integrate AI into their business models and demonstrate value creation are likely to thrive in the evolving market landscape [35]

行业基本情况 证券研究报告：计算机|点评报告 发布时间：2026-01-14 行业投资评级 强于大市|维持 | 收盘点位 | | 6063.95 | | --- | --- | --- | | 52 | 周最高 | 6063.95 | | 52 | 周最低 | 3994.26 | 行业相对指数表现（相对值） -4% 2% 8% 14% 20% 26% 32% 38% 44% 50% 2025-01 2025-03 2025-06 2025-08 2025-10 2026-01 计算机 沪深300 资料来源：聚源，中邮证券研究所 研究所 分析师:陈涵泊 SAC 登记编号:S1340525080001 Email:chenhanbo@cnpsec.com 分析师:李佩京 SAC 登记编号:S1340525080003 Email:lipeijing@cnpsec.com 分析师:王思 SAC 登记编号:S1340525080002 Email:wangsi1@cnpsec.com 近期研究报告 《国产 AI 或将全面超越》 - 2026.01.12 政策吹响号角，AI 驱动工业软件迈向"智变"关 键期 ⚫ 政策加 ...

Core Insights - The article discusses the performance of the Hongyi Yuanfang Consumption Upgrade Mixed Funds C and A, which experienced declines of 7.39% and 6.93% respectively in 2025 [1][2]. Fund Performance - Hongyi Yuanfang Consumption Upgrade Mixed C had a cumulative unit value growth rate of -7.39% with a net value of 1.1630 yuan and a scale of 0.55 billion yuan, established on December 9, 2021 [2]. - Hongyi Yuanfang Consumption Upgrade Mixed A recorded a cumulative unit value growth rate of -6.93% with a net value of 1.1872 yuan and a scale of 0.13 billion yuan, established on January 30, 2019 [2]. Fund Manager Background - The current fund manager, Zhang Jian, has a diverse background including roles at Shanghai Bank and various positions at Huatai Asset Management and Huatai Baoxing Fund Management [1]. - Zhang Jian has been managing public funds since 2006, initially focusing on fixed income, and began managing equity funds in July 2022 [1].

Group 1: Market Overview - The domestic market indices showed positive performance with the Shanghai Composite Index closing at 4,120.43, up by 0.92%, and the Shenzhen Component Index at 14,120.15, up by 1.15% [4]. Group 2: Industry Commentary on AI and Manufacturing - The Ministry of Industry and Information Technology, along with seven other departments, released the "Implementation Opinions on 'Artificial Intelligence + Manufacturing'" on January 7, aiming for significant advancements in the industrial AI sector by 2027. The goals include the deep application of 3-5 general large models in manufacturing, the creation of 100 high-quality datasets, and the cultivation of 2-3 globally influential enterprises [6]. - The opinions detail specific requirements in areas such as computing power, models, data, and application scenarios. For instance, it emphasizes breakthroughs in high-end training chips and intelligent cloud operating systems, as well as the development of industry-specific models [6]. - The report anticipates that the implementation of these opinions will accelerate the penetration of large models across the entire manufacturing process, enhancing areas such as design, production, and management [6]. - The penetration rate of AI applications in Chinese industrial enterprises is projected to rise significantly, from 9.6% in 2024 to 47.5% in 2025, with further rapid growth expected in 2026 due to policy support [6]. Group 3: Investment Recommendations - The report suggests focusing on companies involved in industrial AI applications, such as Zhongkong Technology, Kingdee International, and others. Additionally, it highlights opportunities in data annotation and AI computing power sectors [6].