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Alibaba’s AI cloud growth surge drives earnings despite soaring tech spending

Alibaba Group Holding on Thursday reported revenue growth of 45 per cent for its cloud and artificial intelligence division in the June quarter, driving adjusted profit to a better-than-expected 27.3 billion yuan (US$4 billion). AI Cloud and Compute Services, the Chinese tech giant’s new business segment covering its cloud business and T-Head chip arm, posted 48.4 billion yuan in revenue for the…

Alibaba’s AI cloud growth surge drives earnings despite soaring tech spending

Alibaba Group Holding reported a 45 percent surge in revenue for its cloud and artificial intelligence division in the June quarter, leading to adjusted profit that exceeded expectations. The AI Cloud and Compute Services segment, which includes Alibaba's cloud business and T-Head chip arm, posted record-breaking revenue of 48.4 billion yuan for the quarter, marking its fastest growth in 22 quarters.

This segment's AI-related products generated 12.4 billion yuan in revenue, maintaining triple-digit growth for the 12th consecutive quarter. The Chinese tech giant's total revenue increased by 9 percent year on year to 269 billion yuan, aligning with Bloomberg's consensus estimate. Despite this growth, adjusted Ebitda decreased by 30 percent year on year to 27.3 billion yuan, falling short of the analyst consensus forecast of 26.6 billion yuan.

Capital expenditure rose by 75 percent from the previous quarter to 67.7 billion yuan. The company's free cash outflow more than doubled to 44.7 billion yuan. Alibaba's shares fell 4 percent pre-market following the earnings announcement, while Hong Kong-listed shares rose 1.6 percent to HK$126.2 ahead of the release. Alibaba's restructuring of its reporting segments into four main units – E-commerce Group, AI Cloud and Compute Services, AI Labs and Applications, and Others – aims to better integrate its commerce and AI businesses.

Written by urgent.news from SCMP Business's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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