Alibaba, China's largest e-commerce corporations, saw its net profit plunge in the second quarter this year as it sharply expanded investment in artificial intelligence (AI) infrastructure. Despite a short-term deterioration in profitability, Alibaba said it will continue aggressive investment, making AI a core growth driver.
On the 20th (local time), Bloomberg and other outlets said Alibaba's second-quarter net profit was 10.44 billion yuan (about 2.1 trillion won), down 75% from a year earlier. Capital expenditures in the same period were 67.67 billion yuan (about 13.9 trillion won), up 75%. Converted into dollars, it is about $10 billion.
Revenue rose 9% to 268.95 billion yuan (about 55.5 trillion won), helped by growing demand for computing resources. In particular, revenue from external customers in the cloud institutional sector increased 45%, marking the highest growth rate in 22 quarters.
Alibaba is concentrating investment across the AI ecosystem, including its own AI model "Qyuan," data centers, and semiconductors. In Feb. last year, it announced a plan to invest more than 380 billion yuan over three years in related fields.
Wu Yongming, Alibaba chief executive officer (CEO), projected that a shortage of AI computing power will continue until before 2030. He also emphasized that the funds invested in cloud computing facilities can be recovered within 2 years and 6 months to 3 years. The plan is to expand the application of in-house developed chips in data centers to reduce external procurement expense and improve revenue.
Rival Tencent also expanded second-quarter capital expenditures to 52.8 billion yuan, up 65.5% from the previous quarter. However, unlike its 11% increase in revenue, net profit growth rate remained at 0.7%.
China's big tech companies are deploying cash secured from existing businesses such as e-commerce and games into building AI infrastructure as they move to secure leadership in the cloud market. It is a strategy to accept a short-term decline in profit to preempt computing capacity. However, if large-scale facility investment does not lead to actual customer demand and revenue growth, the burden of depreciation and operating costs could increase. The success or failure of the AI investment race is expected to hinge on the speed of investment recovery and the performance and cost competitiveness of in-house chips.