电子：“人工智能+”政策解读，新质生产力发展路径清晰

Investment Rating - The investment rating for the industry is "Positive" (maintained) [2] Core Insights - The report emphasizes the significance of the "Artificial Intelligence +" policy issued by the State Council, which aims to elevate China's digital economy from connectivity to intelligent driving, marking a qualitative leap in productivity [6][8] - The policy outlines three developmental stages with specific targets for 2027, 2030, and 2035, indicating a clear path for the integration of AI into various sectors [7][8] - The report identifies six key actions to accelerate AI implementation across different domains, focusing on the integration of AI with economic and social development [9][10] Summary by Sections 1. "Artificial Intelligence +" Policy Interpretation - The policy aims to deeply embed AI into production, governance, and innovation, transforming the operational logic of the economy and society [6][8] - It represents a strategic shift towards a new productivity paradigm, building on previous initiatives like "Internet +" [6][8] 1.1 Three-Stage Goals - The goals set for 2027 include widespread integration of AI in six key areas, with a target application penetration rate exceeding 70% [7] - By 2030, AI is expected to fully empower high-quality development, with application penetration exceeding 90% [7] - The 2035 goal envisions a transition to an intelligent economy and society, supporting the realization of socialist modernization [7][8] 1.2 Six Key Actions - The six actions target AI applications in various sectors, including technology, industry, consumer quality, public welfare, governance, and global cooperation [9][10] - These actions aim to promote deep integration of AI with economic and social systems, facilitating large-scale applications [9][10] 1.3 Basic Support Capabilities - The report highlights eight foundational capabilities necessary for AI development, including model enhancement, data supply innovation, and computational power coordination [27][29] - Emphasis is placed on the importance of model quality, data diversity, and computational resources as pillars for AI advancement [29] 2. Investment Layout Directions - The report suggests focusing on infrastructure, AI applications, edge devices, and the integration of AI with emerging technologies as key investment areas in the current A-share market [46][49] - Infrastructure is highlighted as critical, with a surge in demand for computational power driven by the growth of generative AI and industry-specific models [49] - AI applications are transitioning from concept validation to value creation, with a focus on matching technology maturity with industry needs [50] - Edge devices are identified as a significant area for growth, particularly in smart connected vehicles and AIoT [51]