AI步入“立体化变革”深水区 “AI+”时代的中国路径逐渐清晰
Zhong Guo Jing Ying Bao·2025-12-01 16:52

Core Insights - The core viewpoint of the articles emphasizes China's transition in AI development from a focus on "technical frenzy" to "systematic construction," highlighting the importance of governance, practical applications, and talent cultivation in the AI ecosystem [1][7]. Governance as Anchor - The concept of "good governance" is central to China's AI governance strategy, advocating for a balance between technology and ethics, ensuring AI systems align with human values [2][3]. - The governance framework proposed includes "cultural alignment" with three layers: value alignment, institutional alignment, and philosophical alignment [2]. Industry Integration - The integration of AI into the real economy is seen as crucial, with a target set for 2025 to achieve deep integration across six key sectors, leading to a smart economy by 2035 [4]. - China is undergoing three efficiency revolutions: model efficiency, computing efficiency, and data efficiency, which are expected to drive the "AI+" initiative [4]. Talent Development - Talent cultivation is identified as a critical bottleneck in the "14th Five-Year Plan," with initiatives like the "Innovative Leadership Entrepreneur Enhancement Project" aimed at addressing the skills gap among entrepreneurs [6][7]. - The project focuses on immersive learning and practical problem-solving to equip entrepreneurs with the necessary AI knowledge and skills [6]. Practical Applications - Companies like Tencent are already seeing significant improvements in efficiency through AI applications in various sectors, such as advertising and customer service [5]. - The emergence of new roles and the need for a restructured workforce to accommodate AI integration are highlighted, raising questions about labor rights and education reform [5][6]. Conclusion - China's approach to AI development is characterized by a multi-dimensional evolution, integrating governance, practical applications, and talent development to navigate the challenges and opportunities in the AI landscape [7].