途虎AI 能力领跑行业！用户服务、门店运营、供应链等多项应用落地

Core Viewpoint - AI is no longer an optional enhancement but a necessary element for high-quality development in the automotive aftermarket, as emphasized by Tuhu's Vice President Zhang Yue at the 10th Automotive Service Chain Development Forum [1]. Group 1: AI Applications - Tuhu has explored AI technology in three areas: user service, store operations, and supply chain management [1]. - AI customer service utilizes large language models to understand user inquiries through text, images, and videos, providing tailored product recommendations [1]. - AI training employs digital humans and generative AI to automatically create training videos, quickly addressing store training needs and enhancing service quality [1]. - AI operations leverage self-developed image recognition technology to analyze store environments and operational details in real-time, simplifying store management [1]. - AI supply chain uses algorithms to predict inventory needs based on store sales and product models, dynamically adjusting stock levels to reduce excess inventory and ensure timely product delivery [1]. Group 2: Business Growth and Performance - The integration of AI across various scenarios has significantly driven core business growth for Tuhu [2]. - As of the 2025 mid-term financial report, Tuhu's transaction user count reached 26.5 million, a year-on-year increase of 23.8%, with a repurchase rate of 64% and a customer satisfaction rate exceeding 95% [2]. - The number of Tuhu's nationwide stores increased to 7,205, with approximately 90% of stores open for over six months achieving profitability [2]. - The next-day delivery rate for parts exceeded 83%, while the fulfillment cost rate decreased by 0.5 percentage points year-on-year [2]. Group 3: Future Outlook - Tuhu aims to continuously iterate its AI capabilities to help franchisees reduce costs and improve efficiency [2]. - The company plans to collaborate with upstream and downstream industry players to promote intelligent upgrades, contributing to a more standardized, transparent, and efficient development phase for the industry [2].