Cheetah Mobile Inc. Q1 FY2025 earnings call

• Revenue grew significantly, with total revenue up 36% Y/Y and 9% Q/Q. Internet business up 46% Y/Y, AI and Recovery segment up 23% Y/Y and 30% Q/Q. • AI Agents are a game changer, with smart enhancements making products more efficient and user-friendly, e.g., launching AI tool app for document summarization. • Invested in R&D, with AgentOS as next-gen voice system for service robots, tested with distributors and seeing positive customer feedback. • Improved operational efficiency, with AI coding part of daily workflow and robotics prioritizing scalable use cases. • Balance sheet strong, with cash and cash equivalents of approx USD 234 million and long-term investments of about USD 112 million as of March 31, 2025. • Head count reduced to approximately 815 from 860 a year ago through cost control.

In Q1 2025, total revenue reached RMB 259 million, up 36% year-over-year and 9% quarter-over-quarter. The Internet business saw a 46% year-over-year revenue increase. The AI and Recovery segment grew 23% year-over-year and 30% quarter-over-quarter. Gross profit increased by 67% year-over-year and 10% quarter-over-quarter to RMB 190 million. Operating margin of the Internet business nearly doubled year-over-year to 15.5%. Losses from the AI and other segment narrowed to RMB 46 million, compared to RMB 82 million a year ago and RMB 228 million in the previous quarter.

• Expect further margin expansion and continued loss reduction. • Continue disciplined and focused AI investment. • Goal to reach breakeven while maintaining healthy cash position. • Invest in AI to support sustainable long-term value creation.

• Challenges in converting human labor-related data to robotic data in robotics industry. • Data factory productization in robotics still in early stage, not yet significantly contributing to productization. • Risk of being marginalized by platform-based products in AI application layer due to potential slower platform adaptation to technological changes.

Q: We noticed 2 directions of AI in this financial report. From the perspective of strategic resource investment and revenue contribution in the next 3 years, will Cheetah's future development focus more on building an AI tool matrix and focusing on improving AI efficiency on the C-side, or will more resources be invested in robots? How do you balance the differences between these 2 directions?

A: The AI tool matrix is an area to generate benefits quickly this year. Robots are a long-term development direction. Technical challenges of both are similar in final productization of AI technology in enterprises. AI tool matrix is short, flat, fast with faster commercialization rhythm. Robots involve hardware and deeper moat but are long-term task.

Q: The Robotics division is making construction of a data factory. Could you share the company's thoughts on data asset construction and self evolution? Do you consider providing data externally or forming a B2B service in the future?

A: In robotics industry, converting human labor-related data to robotic data is difficult. Data factory productization in robotics is in early stage. Current accumulated data hasn't significantly contributed to productization, but doing exploratory research. No plans to provide data externally or form B2B service in foreseeable 3 years as it's still early stage.

Q: How does the company balance the use of open source models and the self-developed approach in actual deployments, especially in terms of inference efficiency, security and controllability and cost structure?

A: Most companies use open source models if suitable to save resources. Prioritize inference efficiency for commercial scenarios. Cost structure is manageable. Moat in robot business should be built on scenario data assets as most companies' advantages lie in scenario data assets rather than model capabilities.

Q: What considerations does the company have regarding the commercialization path of AI tool applications. Will it consider the user subscription system?

A: AI tools' business model is mainly subscription-based as users are willing to pay for improved efficiency. User subscription model is clear choice. Have been converting tools to subscription model, focusing on user experience. Will use agent technology to transform traditional Internet businesses and make innovative attempts in agent era.

Q: What progress has the company's robots made this quarter? From an industry perspective, what significant changes have taken place in the robot industry this quarter?

A: Robots have started to be used as tour guides in corporate exhibition halls and urban service centers. Industry change: humanoid robots still far from real commercialization, but rise of robots for specialized scenarios. Cheetah focuses on integrated interaction experience, multilingual capabilities, and will launch companion robots for elderly care scenarios.

Q: Will the company achieve overall breakeven in the second half of 2025? What are the main driving factors behind Internet business revenue growth?

A: Achieving breakeven in second half is internal goal, depending on progress of core businesses. Future profitability drivers from AI and other businesses. Internet business growth driven by transition from traditional advertising model to user payment model, enhanced product strength, and expansion of partners and channels with AI empowerment.

Q: The losses of the AI and other business segments significantly narrowed in Q1. What were the main areas where investment was scaled back?

A: Scaled back large-scale model training for certain models as realized it's not significant for company size. R&D became more efficient. Some exploratory projects phased out, transitioning to ROI-oriented approach. Still need exploratory projects but with clear ROI focus.

Q: With the capabilities of large models at home and abroad gradually converging, what are Cheetah's competitive advantages in the AI application layer?

A: Products made with agents bring new user experience, difficult to be marginalized by platforms. Can form new perception for users. Benefits from advancement of large model capabilities. Can quickly seize technological change opportunities to form growth flywheel that platforms can't replace.