Alibaba remains top pick as China AI cloud demand grows: report

The broker maintained its overweight call on China’s internet sector.

UOB Kay Hian maintained its overweight rating on China’s internet sector, with Alibaba as its top buy, as artificial intelligence adoption drives stronger demand for cloud services and large language models.

The broker said AI Cloud remains its preferred segment, supported by rising token demand, improving cloud pricing power, and wider use of AI assistants.

Over the next six to 12 months, it expects key themes to include intensifying LLM competition, faster cloud revenue growth, margin expansion, agentic AI-driven super apps, and vertical-specific LLM monetisation.

Competition in China’s LLM market has intensified following DeepSeek’s open-source V4, alongside releases from Alibaba’s Qwen, Tencent’s Hunyuan, Moonshot AI’s Kimi, and MiniMax. UOB Kay Hian highlighted DeepSeek’s competitiveness, citing its 1m context window, strong intelligence ranking, and pricing advantage.

Token demand has also accelerated in 2026, driven by broader AI adoption, faster model development, 24/7 AI agents, and enterprise use of AI models. The broker said Chinese models are gaining share in global token usage as performance gaps narrow.

Cloud demand is outstripping supply in both China and the US. However, UOB Kay Hian said Chinese hyperscalers have more room to invest, with capex at around 60% of operating cash flow, compared with about 90% for US peers.

Alibaba was maintained at Buy, with a target price of HK$192. The broker said Alibaba is China’s only listed company with full-stack AI capabilities across cloud infrastructure, AI models, and proprietary hardware. It expects Alibaba’s cloud revenue to grow 40% YoY in FY2027.

Tencent and Baidu were also kept at Buy, with target prices of HK$728 and HK$170, respectively. UOB Kay Hian said Tencent could benefit from agentic AI use cases, whilst Baidu’s outlook is supported by cloud growth and potential revenue from its Kunlun AI chip.

Key catalysts include faster cloud growth, progress in self-sufficient chip development, AI integration across businesses, and LLM monetisation in traditional industries.

Risks include regulation over security and privacy, heavy capex and R&D costs, and limited access to high-performance GPU chips due to geopolitical tensions.