AI Goes Big in China: UBS Shares Top Plays for Investors?

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Introduction: What’s going on with AI & China

AI (especially generative AI and “agentic AI” systems/agents that can independently plan and perform tasks) is increasingly moving from hype to revenue‑opportunity in many markets. UBS believes China is approaching a key inflection point. A model called DeepSeek has been a catalyst: its breakthroughs are pushing expectations that large language models (LLMs), agentic AI, and AI‑driven enterprise software in China will become more monetizable, more cost‑efficient, and more widely adopted. UBS projects that 2026 may be the year when AI agents in China really start generating meaningful revenues.

What is “AI monetization” here

Agentic AI / AI agents: These are AI tools or systems that can autonomously carry out tasks (planning, execution, decision‑making) rather than just being used passively. Examples: document analysis, travel planning, enterprise assistants, automating business workflows.
Enterprise applications: AI being embedded in enterprise software (HR, finance, customer support, supply chain) this tends to bring subscription or contract revenues, recurring income, higher margins. UBS sees more of this ahead in China.
Data centers / cloud infrastructure: Underlying infrastructure (servers, data centers, cloud platforms) needed for training, serving, hosting AI models. These are costly, but also offer scale economics and are essential parts of the monetization chain. UBS sees China’s data center/IDC (Internet Data Center) operators as increasingly important. Software tools, “agent frameworks,” AI‑native startups: Tools & frameworks to build AI agents, startups riding generative/agentic AI, and more open‑source / low cost models.
Regulatory & valuation catalysts: Things like approval of data center REITs, more favorable regulation or support, more acceptance of enterprise AI billing models, etc. These serve as triggers that could accelerate monetization.

UBS’s Projections / Expected Upsides for China

Based on what they report: They expect that Chinese AI agents could start generating real revenues by 2026. China’s AI spending is expected to grow significantly: infrastructure, model development, agent deployment. UBS forecasts “low‑teen” annual return potential over coming years for Chinese AI stocks (once some of the monetization catches up) though not as high as for some global AI / U.S. AI peers.

Which “China Plays” UBS Favors

Large Internet / Cloud Majors

Alibaba, Tencent, possibly ByteDance etc.
They have scale, data, capital to invest in AI R&D and infrastructure. They are pushing agent frameworks, offering cloud/AI‑agent tools, building capability to monetize.

Data center / IDC operators

GDS, VNET (and similar) firms hosting large infrastructure for AI, high‑power racks, etc.
UBS sees valuations of some of these having fallen too far; expects fundamentals to rebound with AI‑driven orders. Also development of REITs (real estate investment trusts) for data centers could help.

Enterprise software / AI tools providers

Companies that build & embed AI into business operations (HR, customer support, finance, supply chain). Also “agent frameworks.” Examples named include Yonyou, Kingdee, Kingsoft Office, etc.
These can scale, have recurring revenue models, and can benefit from increased adoption in enterprises. UBS also noted that these firms are already winning orders.

Financials, insurance, brokerage sectors

Financial institutions in China (brokerage / insurance) as these have many “language‑based roles” and high costs currently that can be reduced via generative AI.
UBS forecasts that AI could lead to large cost savings (lower labor cost), higher profits (brokerages up ~8%, insurance up ~13%) from generative AI implementation.

Risks / Challenges

Regulatory / policy risk: Restrictions on technology, data privacy, export controls, possible regulatory tightening. Could affect how, and how fast, companies can deploy or monetize AI.
Model sophistication & capability: Some current AI agents or models are not yet “good enough” in terms of performance, which limits what customers are willing to pay. UBS believes improvements (like DeepSeek’s newer models) are needed.
Monetization habits / culture: In China, business customers are less accustomed to subscription‑based enterprise software/AI tools many AI usages have so far been consumer‑facing, or built‑in free/partially free. Moving to paying models for enterprise AI may take time.
Valuations & expectations are somewhat elevated in some cases: UBS cautions that for some China AI stocks, a lot of upside may already be priced in, so returns may be “low‑teen” not super‑aggressive.

What This Means for Investors / What to Watch

1. Progress of AI models in China (e.g. DeepSeek’s newer models) their capabilities, adoption, benchmarking.
2. Moves by large tech/Internet/cloud companies to build/buy agent frameworks.
3. How data center infrastructure demand evolves both in terms of capacity and in terms of policy support (REIT structures, approvals).
4. Contract wins among enterprise software companies (financials, customer service, supply chain, etc.) seeing recurring revenues from AI tools.
5. Regulatory clarity rules around data privacy, cross‑border data, export controls, AI governance.
6. Financial metrics: margins, free cash flow, capex requirements, how fast investment is paying off.

Advantages & Benefits of AI Monetization in China (UBS View)

Unlocking Enterprise Value

The monetization of AI, especially agentic AI and generative AI, will help companies across sectors reduce operational costs, boost productivity, and improve service efficiency. Enterprises that adopt AI in functions like HR, finance, logistics, and customer support can automate repetitive tasks and generate significant savings. This opens new recurring revenue streams for software vendors and tech providers.

Cost Reduction Across Financial Services

UBS highlights that China’s insurance and brokerage industries are particularly well-placed to benefit. AI agents can automate tasks like claims processing, underwriting, customer service, and financial advisory. This could boost insurance company profits by 13% and brokerage profits by 8%, purely from cost reductions.

Scalability of AI Cloud Infrastructure

The rapid growth of AI requires vast computing power and storage. Chinese data center providers (like GDS and VNET) benefit from this surge in demand. As more enterprises adopt AI, they’ll need high-performance computing, leading to strong growth in AI infrastructure-related revenues.

Enterprise Software Boom

Software providers such as Yonyou, Kingdee, and Kingsoft Office are embedding AI into their enterprise tools. This not only increases the stickiness of their products but allows for SaaS-style monetization (subscription or usage-based models), offering predictable, high-margin revenue.

China’s Own AI Ecosystem Maturing

AI models like DeepSeek are proving China’s capability to build competitive, localized large language models (LLMs). This reduces dependence on foreign AI providers, aligns with national security goals, and allows companies to scale their own AI solutions, especially in regulated sectors.

Policy Support & Regulatory Tailwinds

The Chinese government is promoting domestic tech development and digital transformation, including AI. Measures like approving data center REITs, offering cloud computing subsidies, and encouraging digital adoption in SMEs are all contributing to a more fertile monetization environment.

Massive Market Potential

China has a vast and diverse enterprise base from massive SOEs to tech-savvy private companies. As digital transformation spreads beyond top-tier cities into smaller urban and rural areas, the addressable market for AI-powered solutions will continue to expand.

Faster Time to Market with Agentic AI

AI agents can automate complex, multi-step tasks, reducing development cycles and speeding up delivery of services. Businesses that integrate AI agents into their platforms will see faster turnaround and customer engagement, which enhances competitiveness.

Investment Rebound Potential

Many China tech and AI stocks have underperformed due to macro risks and regulatory headwinds. UBS believes that AI monetization could serve as a re-rating catalyst, bringing renewed investor attention and capital inflows into select names.

Pros and Cons of AI Monetization in China

Pros

Recurring Revenue Models: SaaS-like AI applications generate steady income from subscriptions or usage fees, improving financial visibility.
Infrastructure Demand Surge: Data center operators benefit directly from the growing need for GPU-rich, AI-ready hosting solutions.
Cost Efficiency Gains: AI agents reduce labor costs and improve decision-making speed, especially in financial services, e-commerce, and logistics.
Localized AI Development: China’s own models (e.g., DeepSeek) reduce reliance on U.S. tech and comply with domestic data rules.
Enterprise Digitization Push: A wide base of enterprises in China is undergoing digital transformation, which AI can accelerate.
Government Support: Policy backing for AI development, funding, and pilot zones creates a friendly ecosystem for adoption.
Attractive Valuations: Many Chinese AI and tech stocks trade at lower multiples than U.S. peers, offering value upside if monetization improves.
Export and Ecosystem Potential: Chinese AI models and tools could also be exported to Belt and Road countries or emerging markets, expanding TAM (Total Addressable Market).

Cons

Regulatory Uncertainty: The Chinese tech landscape is still susceptible to sudden regulatory shifts, which can impact monetization timelines.
Slow Enterprise Adoption: Many Chinese enterprises are price-sensitive and still getting used to paying for software or AI tools.
Infrastructure Cost Burden: AI models require massive capital expenditure on chips, data centers, and compute power, which may hurt margins short-term.
Model Maturity Gaps: Not all local AI models match the capability of global peers (e.g., OpenAI, Google), which may delay monetization.
Intense Competition: Multiple players are rushing into AI, leading to fragmentation, pricing pressure, and challenges in building sustainable moats.
Geopolitical Risks: U.S. export restrictions on advanced chips (e.g., NVIDIA GPUs) could slow down China’s AI infrastructure growth.
Customer Monetization Culture: Unlike in Western markets, Chinese consumers and businesses are more used to free tools, making it harder to charge premium AI subscription fees.