Hong Kong stocks rally for fifth day; Morgan Stanley sees China consumer AI revenue reaching 1.6 trillion yuan by 2040

September 22 — Hong Kong's stock market saw a broad rally on Friday, with all three major indices climbing sharply. The Hang Seng Tech Index rose nearly 2% and, if it closes in positive territory today, will mark its fifth consecutive gain. The Hang Seng Index and the Hang Seng China Enterprises Index are both on track for a fourth straight day of gains.

So why is the Hong Kong market strengthening despite the backdrop of U.S. interest rate hikes?

Analysts point to two key supportive factors. First, senior financial officials stated at a symposium with foreign financial institutions that China's economy is generally stable and improving, with ongoing structural optimization and steady progress in high-quality development. Second, AI applications appear to be accelerating. Morgan Stanley estimates that, under a long-term baseline scenario, China's consumer-side AI market could reach approximately 1.6 trillion yuan by 2040. Today, both Tencent and Alibaba made major announcements, and their stock prices showed strong performance.

Hong Kong Stocks Continue to Strengthen

Hong Kong stocks have performed stronger than expected in recent days. On September 22, tech and internet stocks were particularly outstanding:

• Tencent Holdings rose nearly 8%
• Tencent Music surged over 7%
• Alibaba gained nearly 5%
• Baidu rose nearly 4%

In terms of indices, the Hang Seng Tech Index climbed nearly 2%.

Today, Tencent's Hunyuan officially released the Hunyuan Image 3.5 Preview (Hy Image 3.5 Preview) , described as a cost-effective, professional-grade image generation model. The model supports both text-to-image and image-to-image generation, allows up to five reference images per session, supports multiple aspect ratios, and can output at resolutions up to 2K. It also supports multi-turn dialogue-based creation and editing based on historical context.

Separately, at the 2026 Yunqi Conference held today, Alibaba's T-Head Semiconductor unveiled the domestic AI chip Zhenwu V900, which delivers three times the computing power of its predecessor, the Zhenwu M890. A single cluster built on this chip can scale to 500,000 cards, supporting the training and inference of cutting-edge models. Alibaba stated that due to the maturity of T-Head's chip product line and broad customer adoption, annual shipments are expected to increase significantly.

Alibaba Group CEO Eddie Wu said that Alibaba's self-developed M890 AI Super Node is already capable of supporting inference for large models with 2 trillion parameters and has been deployed on a large scale in Alibaba Cloud data centers this quarter. Alibaba is also fully building out its edge-side AI ecosystem, open-sourcing the Qwen 2.7B model and officially launching a mobile-side AI solution for Qwen.

A Potential 1.6 Trillion Yuan Opportunity

In a September research report, Morgan Stanley estimated that the potential monetizable revenue from China's consumer-side AI could expand from approximately 54 billion yuan this year to 294 billion yuan by 2030, and under a long-term baseline scenario, reach about 1.6 trillion yuan by 2040.

Morgan Stanley noted that the revenue structure is heavily skewed toward the merchant side:

• Transaction commissions: approximately 281 billion yuan by 2030
• Advertising: approximately 10 billion yuan
• Subscriptions and pay-per-use: approximately 3 billion yuan

Advertising and transaction commissions together account for about 99% of revenue, with individual subscriptions playing a minor role.

According to a survey by Morgan Stanley's research and data analysis division, AlphaWise:

• 80% of Chinese respondents use AI for personal purposes at least once a week
• 77% of employed Chinese respondents use AI for work weekly
• In the U.S., both figures stand at 54%
• China's generative AI user base has grown from approximately 249 million at the end of 2024 to about 602 million by the end of 2025

Morgan Stanley believes China's advantage lies not in absolute leadership in frontier models, but in super-app distribution, free entry points, mobile payments, and merchant fulfillment loops — embedding AI into high-frequency scenarios such as shopping, food delivery, travel, and content recommendations.

Tencent and Alibaba are listed as core beneficiaries:

• WeChat can integrate conversations, mini-programs, payments, and merchant services
• Taobao can connect recommendations, customer service, price comparison, and transaction conversion with models like Qwen
• Vertical platforms such as Meituan, OTA (online travel agencies), and recruitment sites may also benefit if they master intent-based entry points and execution chains

Morgan Stanley also noted that AI will widen the gap in advertising budget shares across platforms. Major platforms will more deeply embed themselves into the business workflow of "understanding demand — assisting decision-making — completing transactions," using AI attribution to improve conversion rates, frequency, and GMV monetization efficiency.

However, the report also cautioned that the 294 billion yuan figure includes revenue shifted from existing online channels to AI-assisted processes, not entirely new industry revenue. Transaction commissions are based on attributable completed orders and are not double-counted with advertising. The real incremental value depends on conversion rates, repeat purchases, audit standards, and platform commission rates. Given that only about 35% of users are willing to pay for subscriptions, with a maximum average monthly payment of around 41 yuan, consumer AI commercialization is more likely to follow a "user-free, merchant-pays" model driven by commissions and advertising.

Notably, state-owned capital has already taken the lead in AI application deployment. According to a statement released Monday (September 21) by the State-owned Assets Supervision and Administration Commission (SASAC) of the State Council, the SASAC Party Committee recently held a special meeting to deploy measures to accelerate the adoption of AI in manufacturing across central state-owned enterprises.