Tai Mei Ti A P P·2025-11-26 04:09Core Insights - Alibaba is focusing on increasing capital expenditure to enhance future earnings potential, particularly in its AI cloud business, which has shown significant growth despite short-term market concerns [1][6] - The latest quarterly report highlights a 34% year-on-year revenue growth for Alibaba Cloud, driven by strong AI demand and public cloud revenue [1][3] - The company’s capital expenditure surged by 80% year-on-year to 31.5 billion RMB, with a total of approximately 120 billion RMB invested in AI and cloud infrastructure over the past four quarters [1][7] Financial Performance - Alibaba Cloud's revenue reached 39.824 billion RMB, marking a record growth rate [1][3] - Adjusted net profit fell by 72% year-on-year to 10.35 billion RMB, and free cash flow turned into a net outflow of 21.84 billion RMB [1][3] - The total revenue growth for Alibaba Cloud and its non-consolidated businesses accelerated to 34% and 29% respectively for the quarter ending September 30, 2025 [3] AI Business Strategy - The company is prioritizing three key areas for AI development: enhancing core model training capabilities, improving the efficiency of the Bai Lian platform for inference services, and balancing internal AI needs with external customer demands [4][5] - There is a strong demand for AI products among enterprise clients, with significant growth potential in various applications, including product development and customer interactions [3][6] - CEO Wu Yongming expressed confidence in the absence of an "AI bubble" over the next three years, citing solid demand and reasonable return potential [6][7] Supply Chain and Investment Outlook - The global AI server supply chain is experiencing shortages, with demand outpacing supply, which is expected to continue for the next two to three years [7][8] - Alibaba's CFO indicated that the previously mentioned 380 billion RMB capital expenditure plan might be conservative, and further investments could be made to meet market demand [7][8] - The company is focusing on the quality and cost-effectiveness of its AI infrastructure, with various application models contributing to revenue generation [8]