Morgan Stanley vs. UBS: Perspectives on Manus, AI Agents, and China's AI Progress

Introduction

This report compares the perspectives of Morgan Stanley and UBS on Manus, AI Agents, and China's AI progress, based on three key research reports:

1. Morgan Stanley's "Manus and Central Government Work Report: Implications" (March 6, 2025)
2. UBS's "AI Agents: AI Applications' Frontier" (March 6, 2025)
3. UBS's "Golden Age of AI Applications - Could Agentic AI Bring New Opportunities?" (March 6, 2025)

As leading global investment banks, Morgan Stanley and UBS provide valuable insights for investors. This analysis systematically compares their views on AI, offering a comprehensive understanding of the market.

1. Manus: A Comparative Analysis

1.1 Morgan Stanley's Perspective

Key Features and Positioning:

• Manus is a general-purpose AI agent developed by Monica.im, a Chinese startup under Butterfly Effect.
• Unlike conversational AI products like ChatGPT, Manus focuses on task execution.
• It can perform diverse tasks, including report generation, website creation, and online shopping.
• Manus collaborates with third-party LLMs and open-source communities.
• Unlike competitors like OpenAI's Operators and Zhipu's AutoGLM, Manus operates on cloud-based virtual machines.
• It demonstrates advanced goal-setting, self-planning, and task decomposition capabilities.
• Manus outperformed OpenAI Deep Research in all three levels of the GAIA benchmark.

Market Impact:

• Morgan Stanley sees Manus as a positive development for Tencent, reinforcing the shift toward AI 2C applications.
• AI agents like Manus are more advanced than chatbots, integrating reasoning, planning, and execution.
• Manus could accelerate AI adoption in China, benefiting public cloud providers due to its cloud-based operation.
• Its low cost ($2 per task) could drive commoditization in the AI agent market.

1.2 UBS's Perspective

Market Positioning and Capabilities:

• UBS highlights Manus as a "versatile" AI assistant capable of complex tasks like market research, data analysis, coding, and travel planning.
• It notes Manus's strong traction in China, signaling a shift toward reasoning-focused AI development.
• Manus's cost advantage over U.S. leaders like OpenAI could accelerate adoption in China.

Future Outlook:

• UBS views Manus as a precursor to more cost-effective AI agent innovations in China.
• It expects accelerated monetization of "digital employees" and increased VC activity in AI-native startups.

1.3 Key Differences

Depth of Analysis:

• Morgan Stanley provides a detailed technical and market analysis of Manus.
• UBS focuses more on Manus as an indicator of broader AI trends in China.

Market Impact Assessment:

• Morgan Stanley emphasizes Manus's impact on specific companies like Tencent and Alibaba.
• UBS highlights its role in shaping the industry's future direction.

Price Sensitivity:

• Both banks note Manus's cost advantage, but UBS places greater emphasis on this as a driver of adoption.

2. AI Agents: Diverging Views

2.1 Morgan Stanley's Take

Definition and Potential:

• AI agents focus on task execution rather than idea generation.
• They can perform tasks like report generation, website creation, and online shopping.
• Morgan Stanley sees AI agents as a potential "killer app," with Tencent as a major beneficiary.

Impact on Software Industry: Morgan Stanley outlines three scenarios:

1. AI Agents as an Independent Layer: Minimal impact on software but significant on labor markets.
2. AI Agents Integrated into Software: Potential benefits for management software like OA and ERP.
3. AI Agents Replacing Software: Unlikely due to high development costs and consumer habits.

Risks:

• Limited incremental IT budgets despite strong interest in AI adoption.
• Potential disruption of existing software/IT services.
• Macroeconomic deflation could negatively impact enterprise IT spending.

2.2 UBS's Perspective

Definition and Importance:

• AI agents are LLM-driven systems automating workflows and enhancing decision-making.
• UBS sees them as key to future AI monetization, with product launches expected to increase from 2025.

Industry Players: UBS categorizes AI agent players into four groups:

1. Internet/Tech Leaders: Focused on ecosystem integration (e.g., Baidu, Alibaba).
2. Software Companies: Embedding AI agents into product suites (e.g., Yonyou).
3. Device OEMs: Introducing AI agent-like features (e.g., Vivo).
4. Others: Startups and vertical leaders focusing on niche use cases.

U.S. Trends:

• Early adoption in text-heavy workflows like coding and customer service.
• GUI-based agents are emerging, mimicking human-machine visual interactions.
• Strong adoption intent but limited scale due to unclear ROI.

China's AI Agent Applications:

• Chinese software companies launched simple AI agent products in H2 2024, generating revenues of tens to hundreds of millions RMB.
• Common use cases include CRM, ERP, HR, and vertical solutions.
• Pricing is project-based, with recurring revenue from standard modules/PaaS tools.

2.3 Key Differences

Analytical Framework:

• Morgan Stanley focuses on AI agents' impact on the software industry.
• UBS provides a systematic classification of industry players and market opportunities.

Market Maturity:

• Morgan Stanley emphasizes AI agents as a "killer app."
• UBS views them as still in the "early stages," with adoption taking time.

Geographic Focus:

• UBS offers more U.S.-China comparisons.
• Morgan Stanley concentrates on the Chinese market.

3. China's AI Progress: A Comparative View

3.1 Morgan Stanley's Perspective

Government Policy:

• The central government encourages LLM applications, reducing private cloud deployments.
• This shift could benefit public cloud players like Alibaba and Tencent.

Market Landscape:

• Alibaba Cloud and Tencent Cloud hold 27% and 9% of the IaaS public cloud market, respectively.
• Huawei, China Mobile, and China Telecom dominate private cloud deployments.

Technological Breakthroughs:

• Alibaba's QwQ-32B model demonstrates performance comparable to DeepSeek R1 with fewer parameters.
• Manus's capabilities are seen as a significant advancement.

Industry Impact:

• Manus could accelerate AI adoption in China, benefiting public cloud providers.
• Morgan Stanley remains cautious about B2B software companies due to macroeconomic deflation.

3.2 UBS's Perspective

Development Stage:

• UBS sees China's LLM development entering a reasoning-focused phase.
• Manus and DeepSeek-R1's success highlight this trend.

Innovation and Market Expectations:

• Manus's low cost compared to U.S. leaders could drive faster adoption in China.
• UBS expects more cost-effective AI agent innovations in China.

Market Applications:

• Chinese software companies launched AI agent products in H2 2024, targeting large enterprises and state-owned firms.
• Use cases include CRM, ERP, HR, and vertical solutions.

Investment Ecosystem:

• UBS notes active VC activity in AI-native startups.
• Long-term, it favors tech giants with extensive ecosystems, such as Tencent.

3.3 Key Differences

Development Stage:

• Morgan Stanley focuses on specific technological breakthroughs.
• UBS emphasizes China's transition to a reasoning-focused AI phase.

Price Sensitivity:

• UBS highlights cost advantages as a key driver of adoption.

Industry Outlook:

• Morgan Stanley is cautious about B2B software companies.
• UBS is more optimistic, citing vertical application progress.

4. Investment Strategies: A Comparative Analysis

4.1 Morgan Stanley's Strategy

Sector Outlook:

• Bullish on China's internet and services sector; neutral on B2B software.

Stock Picks:

• Alibaba: Bullish due to potential market share gains in cloud infrastructure.
• Tencent: Bullish as a major beneficiary of AI adoption, leveraging its super app WeChat.

Risks:

• Macroeconomic deflation could impact enterprise IT spending.
• AI agents may disrupt existing software/IT services.

4.2 UBS's Strategy

Opportunities:

• Short-term focus on Chinese software companies with vertical AI applications.
• Long-term preference for tech giants with extensive ecosystems, such as Tencent.

Risks:

• Rapid technological changes and intense competition.
• Difficulty in predicting financial outcomes for tech companies.

4.3 Key Differences

Recommendation Clarity:

• Morgan Stanley provides explicit "Bullish" ratings for Alibaba and Tencent.
• UBS offers broader investment themes without specific buy/sell ratings.

Time Horizon:

• Morgan Stanley focuses on mid-term market share shifts driven by government policy.
• UBS distinguishes between short-term opportunities in software and long-term potential in tech giants.

Company Coverage:

• Morgan Stanley emphasizes large internet companies (Alibaba, Tencent).
• UBS provides detailed case studies of smaller software firms (Yonyou, Kingdee, Mingyuan Cloud).

Risk Assessment:

• Morgan Stanley highlights risks like software disruption and labor market impacts.
• UBS provides a systematic risk framework, including technological changes and valuation challenges.

5. Key Takeaways and Future Outlook

5.1 Consensus and Divergence

Shared Views:

1. Manus represents a significant advancement in AI agent technology.
2. AI agents are a critical direction for AI applications.
3. Tencent is well-positioned to benefit from AI adoption.
4. China's AI products have a cost advantage.
5. Use cases like customer service and coding are promising for AI agents.

Key Differences:

1. B2B Software Outlook: Morgan Stanley is cautious; UBS is optimistic.
2. Market Maturity: Morgan Stanley sees AI agents as a "killer app"; UBS views them as still in the early stages.
3. Risk Focus: Morgan Stanley emphasizes disruption risks; UBS focuses on opportunities.
4. Analytical Framework: Morgan Stanley examines policy and market share shifts; UBS focuses on technology and applications.

5.2 Investor Implications

Short-Term Strategies:

1. Monitor government policy impacts on cloud providers like Alibaba and Tencent.
2. Consider Chinese software companies with proven AI agent applications (e.g., Yonyou, Kingdee).
3. Track Manus's market reception as a barometer for AI adoption.

Long-Term Strategies:

1. Invest in tech giants with robust ecosystems, such as Tencent.
2. Assess the potential for AI agents to disrupt existing software markets.
3. Explore opportunities in AI-native startups, especially those with vertical expertise.

Risk Management:

1. Be mindful of macroeconomic deflation's impact on IT spending.
2. Watch for AI agents' potential to disrupt traditional software/IT services.
3. Diversify investments to mitigate risks in the volatile tech sector.

5.3 Future Trends

AI Technology:

1. China's LLM development will continue to focus on reasoning capabilities.
2. AI agent products will proliferate post-2025, with increasing capabilities and adoption.
3. Cost efficiency will remain a key competitive advantage for Chinese AI products.
4. GUI-based agents (graphical user interfaces) may emerge as a significant trend.

Market Dynamics:

1. Government policies favoring public cloud could benefit Alibaba and Tencent.
2. AI agents will accelerate adoption in both enterprise and consumer markets.
3. Industry consolidation may occur, with tech giants acquiring AI startups.
4. Labor markets, particularly in back-office roles, may face disruption.

Investment Opportunities:

1. Short-term opportunities lie in Chinese software companies with vertical AI applications.
2. Long-term, tech giants with extensive ecosystems are likely to dominate.
3. High-value, specialized industries (e.g., legal, finance) offer significant commercialization potential.
4. AI-native startups present high-risk, high-reward opportunities.

Data Sources: Morgan Stanley, UBS Research Reports
Disclaimer: This report is for informational purposes only and does not constitute investment advice.