生成式AI下游ToB应用市场需求有望爆发

Group 1 - Generative AI is becoming a key engine driving the development of new productive forces, with significant exploration space between technological vision and practical application [1] - The white paper released by KPMG China during the 2025 World Artificial Intelligence Conference outlines the internal logic and feasible paths for generative AI to empower industrial transformation [1] - Generative AI has initiated an innovation wave, with the AI core industry scale in China expected to exceed 700 billion yuan by 2024, and over 4,500 related enterprises [1] Group 2 - Companies across various sectors are adopting differentiated practical paths based on specific scenarios, leveraging generative AI's potential to enhance operational efficiency, innovate business models, and reshape product forms [2] - In the internet industry, generative AI has led to the emergence of new business models such as "multi-agent application platforms" and "B-end digital human production lines," significantly improving user experience and operational efficiency [2] - The financial sector is utilizing generative AI for proactive risk assessment, precise retrieval of complex financial data, and automated report generation, showcasing substantial cost reduction and efficiency enhancement potential [2] Group 3 - In industries like automotive, pharmaceuticals, and government, applications such as "intelligent training for sales personnel" and "high-density knowledge scene Q&A assistants" demonstrate the unique value of generative AI in optimizing complex human-machine collaboration processes and enhancing high-value knowledge management [3] - Companies face challenges in embracing generative AI, including unclear strategic positioning, difficulties in integrating technology with business, lagging data governance, insufficient talent reserves, and concerns regarding AI ethics and security risks [3] - The release of value from generative AI is highly dependent on the precise matching of specific industry attributes and scenario characteristics, making the identification of high-value industries and application scenarios a core concern for both supply and demand sides in the generative AI industry [3]