Core Viewpoint - The article discusses the significant AI upgrade that Alibaba's Taobao is undergoing, aiming to enhance operational efficiency while maintaining user experience and business performance. The upgrade focuses on three key areas: improving traffic matching efficiency, reducing costs for merchants, and introducing new AI-driven shopping products [4][8]. Summary by Sections AI Upgrade Strategy - Taobao's decision-making process for the AI upgrade began in December 2024, with three main objectives identified: enhancing search and promotion efficiency, increasing merchant productivity, and launching new AI shopping products. These initiatives are set to roll out starting March 2025 [4][6]. Testing and Implementation - The implementation of new AI features follows a cautious approach, starting with a 2% user test group. If successful, the testing gradually expands to 5%, 10%, and eventually 50% of users before full deployment [5][7]. Major Projects - A significant project is the overhaul of Taobao's product information database, which has accumulated vast amounts of data over 23 years. The introduction of AI agents has enabled the automatic learning and writing of product information, addressing long-standing issues in data quality [6][14]. Performance Metrics - Since the AI initiatives began in March, there has been a notable increase in traffic matching efficiency, with search relevance improving by 20 percentage points and merchant advertising ROI increasing by 12% [7][8]. Upcoming Events - The 2025 Double 11 shopping festival will be the first to fully implement AI features, with several new AI tools already available to merchants [7][8]. AI as a Core Component - AI is positioned as a central theme in Taobao's evolution, with a focus on integrating AI capabilities into existing systems rather than completely overhauling them. This pragmatic approach aims to enhance the search and promotion system, which is critical for e-commerce platforms [11][12]. Infrastructure Development - The product information database is considered a foundational infrastructure for Taobao's future, as accurate and comprehensive product data is essential for effective AI-driven search and recommendation systems [17][18]. Resource Allocation - The company has made significant resource investments in AI, particularly in enhancing the search and promotion system, which is viewed as a long-term strategic initiative [19][20]. Demand-Driven Approach - The AI integration is driven by user needs rather than enforced through rigid performance metrics, allowing for a more organic adoption of AI tools across the platform [21]. Balancing Upgrades and User Experience - The company employs a gradual "cutover" strategy, maintaining both old and new systems simultaneously to ensure a seamless user experience during the transition [22].