2025年：全球贸易又面临重大转折，本期调研主要发现： 首席运营官(COO)对未来挑战有着清醒认0知，1并且清楚地了解阻碍增长的主要外部因素 COO普遍对今年大环境的不确定性有所存疑，但也在寻找潜在推动增长的有效方式。在本次调研中， 有94%的受访者选择新客户(推动需求加速增长)和新产品作为增长途径(见图1)。 然而，研究发现，当前对新渠道的投资热情似乎有所回落。虽然有89%的领先企业将其列为前三大重 点投资方向之一，但相比2024年的93%略有下降。值得注意的是， 区域扩张在企业战略投资布局中 的重要性也出现了下滑，在促进增长的各项领域中，被视为最低优先级 。 1. 首席运营官（COO）对未来挑战有着清醒认知，并且清楚地了解阻碍增长的主要外部因 素。 2. 企业在生成式人工智能（GenAI）领域进展显著：平均而言，有30% 的企业借助GenAI优 化了供应链管理或流程。 3. 随着供应链颠覆与中断的常态化，成本至上的理念将让位于更精细化的资本与风险管理方 法。 4. 执行与规划之间的落差问题更为突出：只有一半的企业开始启动了供应链的端到端转型。 5. 企业各层面技能严重不足，近 40%的COO将其视为当下最 ...

Investment Rating - The industry investment rating is "Positive" (maintained) [1] Core Viewpoints - The report emphasizes the importance of self-reliance in technology due to escalating global trade tensions, highlighting the urgency for core technology products to be self-sufficient [5][12] - National fiscal support is expected to accelerate the implementation of key projects and policies, particularly in the realm of domestic innovation and technology [6][13] - Domestic software and hardware are transitioning from being merely "usable" to "user-friendly," with an anticipated acceleration in replacement cycles [7][14] Summary by Sections Market Review - During the week of March 31 to April 3, 2025, the CSI 300 index fell by 1.37%, while the computer index decreased by 1.87% [4][16] Investment Opportunities - The report suggests that with changes in the global trade environment, domestic software and hardware are on the rise, and the pace of replacement is expected to accelerate. Recommended companies include: - For domestic computing power: Haiguang Information, Zhongke Shuguang, and Shenzhou Digital - For the innovation and creation sector: Kingsoft Office, Dameng Database, Taiji Co., and others [8][15] Industry Dynamics - The report notes significant developments in the industry, including the upcoming release of Alibaba's new model Qwen3 and OpenAI's completion of a $40 billion financing round, which values the company at $300 billion [22][28]

Core Viewpoint - The article emphasizes the critical importance of high-quality, trustworthy data in the financial industry, especially as AI technologies reshape the landscape and increase demand for data [1][2][4]. Group 1: Data Integrity and Management - The financial industry is witnessing a surge in demand for reliable data, with an annual growth rate of approximately 40% since 2019 [1]. - Ensuring data integrity and relevance is essential for large language models (LLMs), as poor data can lead to unreliable AI outcomes, including hallucinations and biases [2][4]. - The implementation of data transparency, security, and integrity is crucial for compliance and building customer trust, exemplified by the use of "watermark" technology in financial data [5][6]. Group 2: Digital Rights Management - Digital rights management is increasingly important, with clients expecting clear definitions of data source availability, AI policy responsibilities, and effective measures against intellectual property infringement [4][6]. - The establishment of a robust framework for digital rights management is necessary to ensure compliance and responsible AI usage [9]. Group 3: Regulatory Framework and Collaboration - The article highlights the need for standardized definitions of "data trust" across the industry to enhance data quality and facilitate its circulation [6][10]. - Collaboration across the industry and the establishment of interoperable regulatory frameworks are key to fostering high-trust AI systems and promoting innovation in the global financial sector [2][10]. - Regulatory initiatives, such as the EU's AI Act and the NIST's AI Risk Management Framework, provide guidance for safe and fair AI practices in the financial services sector [7][11]. Group 4: Future Outlook - The importance of high-quality data will continue to grow as the industry develops AI tools, necessitating a deep understanding from policymakers [8][11]. - The article calls for a collective effort from financial and tech companies, regulators, and users to navigate the challenges posed by evolving AI technologies [11].