HONG KONG (AP) - Alibaba reported a 75% drop in profit for the April-June quarter, landing at 10.5 billion yuan ($1.6 billion), as the Chinese tech giant pours money into artificial intelligence infrastructure. The company's AI cloud and compute services revenue grew 45% to 48.4 billion yuan ($7.2 billion), but capital expenditures jumped 75% to 67.7 billion yuan (about $10 billion), eating into the bottom line.
Quarterly revenue rose 9% to nearly 269 billion yuan (almost $40 billion), according to the Hong Kong- and U.S.-listed company, which started in e-commerce but now positions AI at the center of its strategy. The profit decline compares with 43.1 billion yuan ($6.4 billion) in the same quarter last year.
Why profits fell
Alibaba attributed the spending increase to "fluctuations" in procurement cycles, higher CPU compute capacity in anticipation of growing customer adoption of AI "agents," and higher pricing for chip components. The company's U.S.-traded shares fell more than 3% on Thursday.
"As we continue to ramp up our supply, our AI and Cloud revenue growth will accelerate further in the coming quarters, alongside continued improvement in profitability," CEO Eddie Wu said in prepared remarks during an earnings conference.
Betting big on AI
Alibaba said last year it plans to invest at least 380 billion yuan (about $56 billion) over three years in cloud computing and AI infrastructure. The company has been advancing its flagship Qwen AI model and launched "agentic" AI services for commercial customers. In July, it previewed its Qwen3.8-Max model, which Alibaba said ranked "second only" to Anthropic's Claude Fable 5.
The company has set a goal of surpassing $100 billion in annual AI and cloud revenue within five years. That target explains the current spending pattern: Alibaba is trading short-term profit for long-term position in China's AI infrastructure race. For professionals tracking AI economics, this quarter shows the cost structure behind AI adoption - and the scale at which major players are willing to operate. The financial decisions here mirror broader questions facing executives at companies weighing their own AI investments, from capital allocation to the timeline between spending and returns.
Why this matters for executives and finance professionals
Alibaba's quarter offers a concrete example of the trade-offs in AI investment: revenue growth in AI services does not automatically translate to profit growth during build-out phases. For executives planning AI budgets, the numbers show that infrastructure costs can grow at the same rate as the revenue they're meant to support. Finance teams watching this should note the gap between AI revenue momentum and net income - a pattern that will likely appear in other companies' earnings as AI spending accelerates. Understanding the timing between capital expenditure and returns is becoming a core skill for professionals tracking AI for Finance and larger AI for Executives & Strategy decisions.
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