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AI应用自留地:行业Know-how和本地数据
Guotai Junan Securities· 2025-03-14 11:28
Investment Rating - The report maintains an "Overweight" rating for the industry, consistent with the previous rating [2]. Core Insights - The report emphasizes that the competitive barriers in the AI application landscape are shifting from public information to private information, highlighting the importance of industry-specific know-how and private data for AI service providers [4][25]. - It identifies that enterprise-level AI agents, built on private information, represent the ultimate form of B2B applications, enabling personalized and efficient business solutions [30][33]. - The report suggests that private information services are poised to become a significant business opportunity as AI applications accelerate in the B2B sector [60]. Summary by Sections 1. Transition from Public to Private Information - The report discusses how the barriers in internet applications were historically based on the openness of information, which has now been disrupted by advanced AI models like DeepSeek [1.1][18]. - It notes that the value of public information is diminishing as AI models can utilize vast amounts of data, leading to a new focus on private information as a competitive advantage [1.3][25]. 2. Enterprise-Level AI Agents - The report outlines that traditional B2B applications are limited by clear functional boundaries and lack collaboration, which AI models can help integrate [30][32]. - It highlights that private information is crucial for developing personalized AI applications that can adapt to specific business needs, thus enhancing operational efficiency [35][36]. 3. Potential of Private Information Services - The report indicates that private information services will play a vital role in helping businesses leverage their unique data and industry knowledge to build customized AI workflows [60][61]. - It emphasizes that as companies accelerate their digital transformation, the demand for private information services will grow, creating new business models and opportunities [61][62].