《“人工智能+制造”专项行动实施意见》点评：AI赋能制造业，打造新质生产力

Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - The issuance of the "AI + Manufacturing" action plan aligns with global industrial competition and domestic manufacturing transformation needs, aiming to empower the manufacturing sector with AI technology and establish a new quality productivity base [2][4] - The plan emphasizes the integration of AI into manufacturing processes, which is seen as a critical driver for enhancing China's competitive advantage in core technologies and industrial scale [4][10] - The report outlines a comprehensive development system that includes technical support, scenario empowerment, product innovation, ecological activation, and safety assurance [7][9] Summary by Sections Background and Core Positioning - The deep integration of AI and manufacturing is essential for reshaping industrial advantages and seizing development opportunities amid global competition [4] - The plan aims to accelerate the application of AI in manufacturing, addressing the long-standing issues of "large but not strong" in China's manufacturing sector [4][6] Key Policy Interpretations - The action plan focuses on precise implementation and deep advancement from "AI+" to "manufacturing empowerment," targeting specific sectors and processes within the manufacturing industry [5][6] - It sets a goal for China to achieve reliable supply of key AI technologies and maintain a leading position in industrial scale and empowerment levels by 2027 [6][10] Core Measures - The report identifies five core measures to build a comprehensive development system, including: - Innovation Foundation: Establishing a full-chain technical support system for AI in manufacturing [7] - Intelligent Upgrade: Promoting deep empowerment of AI across all processes and industries [8] - Product Breakthrough: Encouraging the iteration and upgrade of intelligent equipment and new business models [8] - Ecological Cultivation: Activating collaborative innovation among market entities [9] - Safety Assurance: Building a multi-dimensional safety protection system [9] Practical Implications - The action plan addresses the mismatch between computing power supply and manufacturing demand, emphasizing the need for practical applications of AI technologies [10] - It aims to facilitate a fundamental shift in manufacturing from factor-driven to innovation-driven growth, enhancing quality and efficiency [10][13] Challenges and Outlook - The report acknowledges challenges in the deep integration of AI and manufacturing, including performance limitations of industrial models and data fragmentation [11][12] - It anticipates that by 2027, 500 typical application scenarios will be established, leading to scalable implementations in key areas [13]