Dingdong(US:DDL) 虎嗅APP·2025-10-16 00:09Core Insights - The article emphasizes the importance of integrating AI into business operations, particularly in supply chain management, to transform it from a cost center to a value center [5][23][24]. Group 1: AI Implementation in Supply Chain - Dingdong Maicai utilizes Agentic AI to enhance traceability and accountability in its fresh supply chain, addressing issues of high loss, volatility, and time sensitivity [7][8]. - The company has achieved a 95% accuracy rate in sales forecasting for overall orders and popular items, showcasing the effectiveness of AI in decision-making processes [8]. - The approach involves a full-chain upgrade from human-driven processes to algorithm-driven operations, ensuring clarity and accountability at every stage [8]. Group 2: Digital Transformation Strategies - Ningji adopts a light-asset, rapid expansion model, focusing on data-driven decision-making to reduce reliance on individual expertise, allowing the CEO to "work less" [9][10]. - The company emphasizes the importance of completing foundational steps like information and online transformation before advancing to AI applications [10]. - AI applications at Ningji are centered around efficiency and revenue generation, with practical implementations in customer service and site selection [10]. Group 3: Content Supply Chain Innovation - Tezign views content as a new SKU, advocating for a content supply chain that allows for the reuse and combination of creative assets [13][14]. - The company employs AI to manage and produce marketing content efficiently, enabling rapid generation without requiring design skills from operators [14]. - This approach positions content production as a core asset for businesses, moving away from one-time use to reusable modules [14]. Group 4: Gradual AI Integration - Shuhai Supply Chain emphasizes a methodical approach to AI integration, focusing on cost reduction, efficiency enhancement, and quality improvement [15][17]. - The company has invested over 400 million yuan in developing a comprehensive SaaS system to streamline operations across various business functions [17]. - AI implementation is approached in stages, starting with simpler tasks to build a foundation before tackling more complex scenarios [17][21]. Group 5: Industry Challenges and Consensus - Participants in the roundtable discussion highlighted the challenges of aligning consumer demands with supply chain capabilities, particularly in the fashion industry [18][19]. - There is a shared concern about measuring the value of AI, as business growth results from multiple factors, complicating the attribution of success to specific AI tools [19][20]. - A consensus emerged that AI is not a panacea but rather a complex system engineering challenge that requires a structured approach to implementation [20][22].