The new share placement comes as the Chinese company ratchets up quarterly capital spending to almost $10 billion, aiming to safeguard its position in a fiercely competitive global AI arena
Alibaba Group Holding Ltd. is seeking to raise about HK$80 billion ($10.2 billion) from a share sale, its latest move to compete for global leadership in artificial intelligence.
The online retail giant-turned-AI player is offering 710 million shares at HK$112.7 each, according to terms of the deal seen by Bloomberg News. That represents a discount of 3.6% to the closing price of Alibaba’s American depositary receipts on Friday.
The placement would be Hong Kong’s biggest follow-on offering by a company on record, according to data compiled by Bloomberg. It would also be the city’s biggest share sale since 2021, when technology-investment firm Prosus NV sold $14.7 billion in shares of China’s Tencent Holdings Ltd., according to data compiled by Bloomberg.
The deal comes as the Chinese company ratchets up quarterly capital spending to almost $10 billion, aiming to safeguard its position in a fiercely competitive global AI arena. It intends to use the proceeds to invest in full-stack AI capabilities, including by expanding and enhancing its infrastructure.
Alibaba will be subject to a lockup of 90 days. China International Capital Corp., HSBC Holdings Plc, Morgan Stanley and UBS Group AG are arranging the deal, according to the terms.
Hangzhou-based Alibaba’s profit plunged more than 75% for the June quarter to 10.5 billion yuan ($1.6 billion) and it registered a free-cash outflow of $6.6 billion, reflecting the rising cost of AI projects and computing infrastructure.
China’s e-commerce leader this year cemented its status as a global artificial intelligence frontrunner after its flagship Qwen offering became the world’s most popular model family.
Alibaba is among the biggest spenders on AI among its Chinese rivals. The company, a domestic leader in cloud computing, has been hiving off assets and deploying capital toward everything from chips and data centers to large-language model development.
