累计建成数万家智能工厂 "目前，人工智能已渗透领航工厂70%以上的业务场景。"1月21日，工业和信息化部（以下简称"工信部"）新闻发言人、信息通信发展司司长谢存表示，工 信部将支持领军企业探索未来制造模式，持续培育一批领航工厂，引领产业整体变革。推动领航工厂成为技术、标准、规则的策源地，并加速向海外复制推 广，为全球制造业数字化智能化转型提供中国智慧。 2024年，工信部联合五部门启动智能工厂梯度培育行动，构建基础级、先进级、卓越级、领航级四级体系。其中，基础级筑牢数字化底座，先进级实现系统 协同，卓越级为国内领先标杆，需要满足AI应用场景≥20%，领航级则瞄准全球领先、深化AI融合。四级培育体系，能够精准适配不同规模、不同基础的制 造企业转型需求，实现分层进阶、全域提质的发展目标。 2025年底，工信部等六部门联合公布首批15家领航级智能工厂名单，名单涵盖装备制造、原材料、电子信息等多个关键行业。 中国信息通信研究院信息化与工业化融合研究所所长刘默在接受媒体采访时表示，在领航级工厂探索背后，实现的是未来高定制化产品、高复杂度生产，而 且在快速迭代背景下，国家制造还能保持极高的效率、极低的成本和极高的质量。通 ...

Group 1: Market Outlook - Goldman Sachs views Chinese stocks as a key focus area within its global asset allocation strategy for 2026, indicating a bullish outlook for the Chinese stock market [1] - The firm anticipates a sustained "slow bull" market in China, benefiting insurance companies' allocation to equity assets, which is expected to enhance overall investment returns [1] - The current global economic environment, characterized by no recession in the U.S. and ample liquidity, historically favors stock markets [2] Group 2: Earnings Growth Drivers - Goldman Sachs identifies three main themes driving earnings growth in China: AI, overseas expansion, and anti-involution [4][5] - AI is projected to contribute approximately 2% to 3% annual earnings growth for the entire market over the next 3 to 5 years as Chinese tech companies benefit from its application [4] - The overseas revenue share for Chinese companies is currently around 16%, indicating significant room for growth compared to the 28% for S&P 500 companies [5] Group 3: Valuation and Market Performance - The MSCI China Index's current dynamic P/E ratio is approximately 13, aligning with historical averages, while the CSI 300 Index is around 15, also near its historical median [3] - Goldman Sachs forecasts an overall return range of 15% to 20% for the year, driven primarily by earnings growth rather than valuation expansion [3] - The firm expects a substantial inflow of capital into the stock market, estimating around $200 billion in southbound capital flow into Hong Kong stocks this year [6] Group 4: Investment Themes and Strategies - Goldman Sachs maintains a high allocation to AI-related sectors, including software, internet, and hardware, while also favoring materials and insurance [8] - The firm emphasizes the importance of shareholder returns through dividends and buybacks, which have proven effective in other markets [8][9] - The insurance sector is highlighted as a favorable investment due to its stable returns and potential for higher equity asset allocation in a slow bull market [9] Group 5: Investor Sentiment and Behavior - There is a growing interest among overseas investors in the Chinese market, although actual investment actions have yet to materialize [6][7] - The firm notes that personal investors currently allocate only about 10% of their assets to stocks, suggesting a potential shift towards higher equity allocation if the market enters a sustained bull phase [10] - The anticipated improvement in inflation expectations may further drive demand for risk assets among individual investors [10]

Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - The report highlights the significant progress in the development of smart factories in China, with over 15 leading smart factories, more than 500 excellent smart factories, and over 35,000 basic smart factories established, indicating a robust growth trend in the sector [9][10] - The evolution of smart factories is characterized by five core directions: expansion of factory construction, innovation in R&D design paradigms, upgrading of production capabilities, optimization of production management, and advancement in operational management [10][41] - The report emphasizes the need for the manufacturing industry to transition from quantity-driven growth to quality-driven improvements, addressing the challenges posed by global economic slowdowns and changing market demands [17][18] Summary by Sections Overall Trends - The report identifies four main drivers for the transformation of smart factories: industrial upgrades, changing market demands, technological advancements, and international cooperation [17][19] - It outlines a future vision for smart factories that includes the integration of AI across all manufacturing processes, leading to autonomous decision-making and enhanced collaboration within the manufacturing ecosystem [20][41] Industry Practices - The report describes a four-tiered system for cultivating smart factories, which includes basic, advanced, excellent, and leading levels, aimed at promoting digital transformation in manufacturing [41][42] - It notes that over 90% of manufacturing sectors are now covered by smart factory initiatives, with a focus on enhancing traditional industries and empowering consumer-driven sectors [50][49] Regional Development - The report discusses the regional disparities in smart factory development, with eastern regions leading and central regions making breakthroughs, highlighting the importance of localized strategies [12][49] Technology and Industry - The report emphasizes the need for a deep integration of technology and manufacturing systems, advocating for a shift towards a more resilient and intelligent industrial foundation [12][53] Future Outlook - The report envisions a next-generation smart manufacturing landscape characterized by autonomous manufacturing, ecological collaboration, and a focus on sustainability [12][41]

Group 1 - The core viewpoint indicates that the valuation levels of major scale indices have reached above the historical 80th percentile, suggesting a shift in market drivers from liquidity to profit improvement in the future [1] - Since the "9.24" market event, the A-share market has undergone significant valuation recovery, with the valuation percentile of the CSI 500 exceeding 90%, indicating that systemic undervaluation opportunities have largely disappeared [1] - The driving forces for 2026 are expected to continue along the lines of "liquidity + profit," with a notable shift in core drivers likely to dominate the pace of future index increases [1] Group 2 - Profit improvement signals are expected to come from three clear directions: profit recovery in industries such as industrials and materials, sustained domestic demand policies, and continued external demand support from moderate global economic growth [2] - The current index composition reflects a significant increase in the weight of information technology and industrial sectors within major indices like the SSE 50 and CSI 300, while traditional sectors like finance are seeing a reduction in their weight [2] - For 2026, the trading rhythm is anticipated to show an upward trend in the first half due to a favorable combination of a loose liquidity environment and price recovery, particularly benefiting indices with higher allocations in cyclical sectors like the CSI 500 and CSI 1000 [2]

Investment Trends - The "14th Five-Year Plan" period emphasizes investment in traditional industries focusing on high-end, intelligent, green, and integrated development, with a strong push for technological innovation and transformation[7] - Manufacturing investment growth rates from 2021 to 2024 are projected at 13.5%, 9.1%, 6.5%, and 9.2% respectively, indicating a robust investment environment despite external pressures[17] - In 2025, manufacturing investment growth slowed to 1.9%, a decline of 7.3 percentage points from 2024, highlighting a potential downturn in investment momentum[26] Structural Challenges - Investment efficiency has declined, with the incremental capital output ratio (ICOR) rising to approximately 14.9 from 13.1, indicating increased investment required for each unit of output[32] - The capacity utilization rate for major industrial enterprises was 74.6% in Q3 2025, reflecting a 0.5 percentage point decrease year-on-year, suggesting underutilization of resources[30] - Investment in high-tech manufacturing has significantly slowed, with growth rates dropping below overall manufacturing investment in 2024, indicating structural weaknesses in emerging sectors[32] Strategic Recommendations - Establish a dynamic identification system for investment directions aligned with the "14th Five-Year Plan" to enhance investment effectiveness and adaptability[9] - Focus on four key investment areas: upgrading traditional industries, fostering emerging industries, planning for future industries, and optimizing supply in weak links[44] - Emphasize the importance of human capital alongside material capital in investment strategies to enhance overall economic returns[41]

工业和信息化部近日印发《工业互联网和人工智能融合赋能行动方案》，提出到2028年，我国工业互联 网与人工智能融合赋能水平显著提升，推动不少于5万家企业实施新型工业网络改造升级，在20个重点 行业打造一批高质量数据集。 行动方案明确将通过实施基础底座升级、数据模型互通、应用模式焕新、产业生态融通等四大行动，推 动工业互联网和人工智能在更广范围、更深程度、更高水平上释放融合赋能效应。行动方案提出，到 2028年，我国满足人工智能工业应用高通量、低时延、高可靠、低抖动通信需求的新型工业网络规模持 续扩大，在原材料、装备制造、消费品、电子信息等重点行业工业企业加快部署应用。面向重点产业链 关键环节、典型场景，培育一批智能化解决方案供应商，有效推动大中小企业协同升级。重点企业、技 术产品、公共服务等要素资源实现高效配置。 ...

央视网消息："智能"制造是制造业高质量发展的核心引擎。2025年年底，工业和信息化部等六部门联合公布了首批15家领航级智 能工厂名单，名单涵盖装备制造、原材料、电子信息等多个关键行业。首批领航级智能工厂不仅代表着当前中国制造"智能化"的最高 水平，更标志着中国智能制造从数字化、网络化迈向了智能化的关键跃升期。随着制造业数智转型迭代升级，赋能中国制造向全球价 值链高端稳步迈进。 | | | 2025年度领航级智能工厂项目培育名单 | | | | --- | --- | --- | --- | --- | | | 序号 | 企业名称 | 项目名称 | 所在地 | | CCTV 4 | 1 | 宝山钢铁股份有限公司 | 高端绿色硅钢预测式制造 智能工厂 | 上海 | | ■ヌ国际 | 2 | 上海航天设备制造总厂有限公司 | 高可靠规模化字航产品全 液程链动智能工厂 | 上海 | | | 3 | 徐州重型机械有限公司 | 全球定制敏捷交付的移动 式起重机智能工厂 | 江苏 | | | 4 | 南京钢铁股份有限公司 | 产业链深度协同的特殊钢 个性化定制智能工厂 | 江苏 | | | ને | 中国石油化工股份有限公 ...

Core Insights - The Ministry of Industry and Information Technology has issued an action plan to enhance the integration of industrial internet and artificial intelligence, aiming for significant improvements by 2028 [2] Group 1: Action Plan Objectives - By 2028, the plan aims to implement new industrial network upgrades in no less than 50,000 enterprises and create high-quality datasets in 20 key industries [2] - The action plan outlines four major initiatives: upgrading foundational infrastructure, ensuring data model interoperability, renewing application models, and fostering industrial ecosystem integration [2] Group 2: Industry Impact - The plan emphasizes the expansion of new industrial networks that meet the high throughput, low latency, high reliability, and low jitter communication needs of artificial intelligence applications [2] - Key industries such as raw materials, equipment manufacturing, consumer goods, and electronic information are targeted for accelerated deployment of these applications [2] - The initiative aims to cultivate a number of intelligent solution providers focused on critical links and typical scenarios within key industrial chains, promoting collaborative upgrades among large, medium, and small enterprises [2]

Core Insights - The article discusses the implementation of the "Artificial Intelligence + Manufacturing" initiative by eight departments, aiming to accelerate the integration of AI with the manufacturing sector and promote intelligent transformation [2][4] - The Ministry of Industry and Information Technology (MIIT) emphasizes that developing AI is essential for achieving new industrialization, focusing on both technology supply and application empowerment [3] - The initiative outlines seven key tasks and 21 specific measures to enhance the intelligent, green, and integrated development of the manufacturing industry [4][5] Group 1: Key Tasks and Goals - The initiative aims to apply 3 to 5 general large models in manufacturing by 2027, create 100 high-quality industrial data sets, and promote 500 typical application scenarios [4] - It seeks to cultivate 2 to 3 globally influential leading enterprises and a number of specialized small and medium-sized enterprises, establishing a robust ecosystem for AI in manufacturing [4] - The goal is to build a globally leading open-source ecosystem and enhance security governance capabilities [4] Group 2: Industry-Specific Guidelines - The "Guidelines for Key Industry Transformation" provide direction for sectors such as raw materials, equipment manufacturing, consumer goods, electronics, and software services [6] - In the automotive sector, the guidelines emphasize accelerating the intelligent upgrade of the entire supply chain, including the development of automotive large models for design optimization [6] - The integration of AI in manufacturing is seen as a critical factor for driving innovation in research and design, improving production efficiency, and optimizing supply chain management [6][11] Group 3: Industrial Internet and AI Integration - The integration of industrial internet and AI is highlighted as a key driver for new industrialization, with plans to enhance the level of integration by 2028 [7][8] - The initiative includes expanding new industrial networks to meet the demands of AI applications and improving data governance and sharing systems [7] - The focus is on creating a collaborative ecosystem that promotes the application of AI and industrial internet across various key industries [7][8] Group 4: Local Initiatives and Developments - Various local governments are launching their own "AI+" initiatives to drive high-quality development, with specific action plans and targets [9][10] - For instance, Shanghai aims to add 100 manufacturing enterprises with over 1 billion yuan in annual output by 2028 [9] - The establishment of dedicated AI development agencies in cities like Guangzhou and Zhuhai reflects a growing commitment to fostering AI innovation at the local level [10]

Core Viewpoint - The article discusses the implementation of the "Artificial Intelligence + Manufacturing" initiative by the Ministry of Industry and Information Technology (MIIT) and other departments, aiming to accelerate the integration of AI with the manufacturing sector and promote intelligent transformation in the industry [3]. Group 1: Key Tasks and Goals - The initiative outlines seven key tasks including innovation foundation, intelligent upgrade, product breakthroughs, entity cultivation, ecological expansion, safety protection, and international cooperation, with 21 specific measures to enhance the intelligent, green, and integrated development of manufacturing [5]. - By 2027, the goal is to promote the deep application of 3 to 5 general large models in manufacturing, create 100 high-quality industrial data sets, and establish 500 typical application scenarios [5]. Group 2: Industry Transformation Guidelines - The "Guidelines for Key Industry Transformation Empowered by AI" provide direction for sectors such as raw materials, equipment manufacturing, consumer goods, electronic information, and software services [6]. - In the automotive sector, the guidelines emphasize accelerating the intelligent upgrade of the entire supply chain, including the development of automotive large models for design and optimization [6]. Group 3: Industrial Internet and AI Integration - The integration of industrial internet and AI is highlighted as a crucial aspect of the initiative, with plans to enhance the level of integration by 2028, including the deployment of new industrial networks in over 50,000 enterprises [9]. - The article notes that AI is transitioning from being an auxiliary tool to becoming a core engine for industrial internet, enhancing capabilities such as real-time optimization and intelligent scheduling [10]. Group 4: Local Initiatives and Developments - Various local governments are actively promoting AI initiatives, with Shanghai aiming to add 100 manufacturing enterprises with over 1 billion yuan in annual output by 2028 [12]. - The establishment of dedicated AI development agencies in cities like Guangzhou and Zhuhai reflects a growing commitment to fostering AI innovation and integration within local industries [13].