雷峰网·2025-07-08 06:00Core Viewpoint - The competition for "AI tables" in the To B sector is not just about functionality but about establishing authority in AI-driven business solutions [3][4][40]. Group 1: AI Table Market Dynamics - The To C internet's hot topic is instant retail, while the To B sector is focused on AI tables, with major players like Airtable, Notion, and Microsoft leading the charge [3][4]. - Domestic competition is intensifying, with companies like Feishu, Tencent, and DingTalk launching their own AI table products [3][4]. - The AI table represents a new form of productivity tool, leveraging large model technology to address the inefficiencies of fragmented and unstructured business data [6][8]. Group 2: Importance of AI Tables - AI tables are seen as a core form of business data management, essential for generating, storing, and sharing high-value business data [8][10]. - The widespread use of tables in business management provides a natural user base for AI tables, making them a familiar tool for many [9]. - Tables inherently possess data attributes, making them crucial for data-driven decision-making in modern enterprises [10][11]. Group 3: Competitive Landscape - The competition among collaborative office vendors revolves around who can help businesses master core productivity tools [16][18]. - In the era of large models, the definition of core productivity has shifted to more efficient production lines, with tables serving as key carriers of this productivity [17][18]. - AI tables enhance the capabilities of users, allowing even novices to utilize complex data management tools effectively [21][22]. Group 4: Future of AI Tables - AI tables can serve as the foundation for numerous AI applications, transforming fragmented business scenarios into cohesive systems [14][28]. - The integration of structured and unstructured data within AI tables can create a comprehensive knowledge management system for enterprises [31][32]. - DingTalk's focus on AI tables reflects a strategic vision that positions them as essential tools for data production and processing in the era of large models [36][40].