Cheetah Mobile Inc.

First-quarter 2026 revenue was RMB 259 million, roughly stable year over year. Robotics and others revenue increased 175.9% year over year to RMB 51.2 million, accounting for 19.8% of total revenue, while cloud and AI infrastructure revenue rose 68.3% year over year. Operating loss was RMB 28.3 million versus RMB 26.5 million a year ago. Internet service business adjusted operating profit was approximately RMB 15.2 million, and Global Enterprise Services adjusted operating profit was approximately RMB 13.8 million. As of March 31, 2026, cash and cash equivalents were approximately $186 million, with over $100 million in long-term investments. Looking ahead, management said robotics and other revenue should continue growing year over year and quarter over quarter in Q2, with robotics and others plus cloud/AI infrastructure expected to exceed more than 50% of total revenue in the second half of 2026.

Fu Sheng framed 2026 as an important transition year as Cheetah Mobile moves from a traditional internet company toward AI-enabled applications for agents and robotics. He stressed that the company is shifting from capability building to early commercial validation, focusing on practical products that deliver ROI in real business scenarios. His tone was optimistic but grounded, repeatedly emphasizing that real deployment data, scenario-specific execution, and customer demand are the key advantages in robotics and enterprise AI.

Thomas Ren said management is emphasizing operating discipline, better revenue quality, and financial flexibility while investing in AI and robotics. He noted total revenue was RMB 259 million, robotics and others revenue rose to RMB 51.2 million, operating loss widened modestly to RMB 28.3 million, and the Internet services and Global Enterprise Services segments both stayed profitable with adjusted operating profit of about RMB 15.2 million and RMB 13.8 million, respectively. He also highlighted a strong liquidity position of about $186 million in cash and cash equivalents plus over $100 million in long-term investments, which he said supports continued investment in a disciplined and sustainable way.

Analysts focused on the robotics industry’s key moat, training data, commercialization path, and the future structure of robots. Fu Sheng argued that robotics is constrained by a lack of real-world data and by the difficulty of transferring simulation or lab training to physical environments, and he said the real barrier is scenario execution, customer networks, and accumulated deployment data. He also said humanoid robots are unlikely to replace humans in the next 3 to 5 years, while wheeled robots, robotic arms, and practical products like smart wheelchairs are more commercially viable near term. On enterprise AI, he said the moat comes from deep user and industry understanding, fast product iteration, and helping customers change their organizational processes around AI rather than relying only on customized software delivery.