中美AI产品应用生态对比研究：你方唱罢我登场，中美AI应用深度研究

Core Insights - The report highlights the contrasting paths of AI product applications in China and the United States, focusing on sectors such as education, advertising, video generation, and AI agents, indicating that AI is driving cost reduction and revenue growth for leading global companies [1][2]. Group 1: Education Sector - The education sector in China is characterized by an "exam-oriented" approach, focusing on efficiency and score improvement, with representatives like Zuoyebang and iFlytek, while the U.S. emphasizes personalized learning and lifelong education, represented by companies like Duolingo and Khan Academy [4][5]. - China's education strategy is driven by national policy, aiming for rapid AI talent cultivation, whereas the U.S. promotes critical thinking and interdisciplinary skills [5]. Group 2: Advertising and Marketing Sector - In advertising, China leverages a "content-social-e-commerce-payment" closed loop, represented by Douyin and Alibaba, to enhance ad conversion efficiency, while the U.S. focuses on user experience and brand value, with companies like Google and GumGum optimizing content matching and contextual ad placement [6]. Group 3: Video Generation Sector - The video generation sector shows a divergence where China emphasizes efficiency and cost reduction through platforms like Kuaishou and ByteDance, while the U.S. focuses on creative expression and content ecosystem building with companies like Runway and Luma [8][9]. - Chinese tools are designed for high-efficiency generation and integration, while U.S. platforms support modular operations and encourage secondary creation [9]. Group 4: AI Agent Sector - U.S. companies are leading in the integration of AI agents into workflows, enhancing enterprise efficiency, while China's ToB AIGC products are developing more slowly, with companies like Kingdee and Yonyou accelerating their AI service transformation [4][10]. Group 5: Growth Potential of AI Applications in China - China's AI application landscape is poised for rapid growth, driven by rich scene data and decreasing computing costs, with a projected increase in computing resources to over 300 EFLOP/s by 2025 [18][23]. - The report anticipates that 2025 will mark a significant year for AI application deployment in China, similar to the mobile internet boom a decade ago, with a large user base and diverse application scenarios supporting AI model training [26][28].