Alibaba’s (BABA) Qwen artificial intelligence app is set to hold a press conference on Thursday morning that could excite investors, and may even provide new growth opportunities for the tech giant’s cloud unit, Jefferies said.
“Based on media interviews [in November 2025], we expect a number of BABA’s applications such as Taobao, Figgy, Taobao Instant Commerce, and Alipay to be integrated with Qwen app,” Jefferies analyst Thomas Chong wrote in a note to clients. “Users can experience a variety of different services under different scenarios.”
Chong, who has a Buy rating and $225 price target on Alibaba, said the company’s cloud unit is likely to capture “the majority of incremental industry AI cloud revenue.” And with the rise of AI adoption and AI agents, Alibaba Cloud could grow revenue sharply in 2026.
“Based on our estimates, industry revenue growth is 149% YoY and BABA captures 40% market share in 2025,” Chong explained. “Alibaba Cloud aims to capture 80% of incremental industry revenue growth in 2026. If we assume industry growth can maintain at high double-digit or triple-digit YoY growth in 2026, we expect BABA continues to maintain strong YoY growth momentum at triple digit with market share to reach about 60% this year.”
According to research firm Omdia, AI revenue for cloud computing is expected to increase by 149% year-over-year from RMB20.83B in 2024 to RMB51.8B in 2025. In Alibaba Cloud was first in AI cloud revenue and had roughly 35.8% of the market, more than the second, third and fourth players, combined.
And with Qwen getting more attention (as it provides not only Q&A, but pricing comparison for Taobao, navigation for Amap and various other Alibaba offerings), there is a huge runway for growth.
“There are about 70% of customers using both its API and GPU services,” Chong posited. “On the other hand, enterprises which have their own datasets use Alibaba Cloud for fine-tuning, pre- and post-training. AI is widely used across different industries, with increasing adoption in various parts of operations. There are still over 90% of enterprises yet to embrace AI opportunities. Examples include: enterprises (auto/financial) use 20–30 years of in-house data training their models; unlock AI potential such as the use of visual large models to measure and identify issues (agriculture); improve productivity in resume screening and tie for interview (recruitment). Limited revenue contribution from [mapping-as-a-service] under AI Cloud revenue. There is significant potential to be unlocked.”