Morgan Stanley has released a report expressing skepticism about whether OpenClaw-related products can achieve large-scale adoption in mainland China at this stage. The firm indicated that the framework remains an experimental autonomous agent framework, rather than a mature application ready for direct consumer use. In its current form, challenges related to ease of use, reliability, and security continue to pose significant obstacles. Morgan Stanley noted that differentiation among various products based on OpenClaw is limited, with core functions primarily focused on "one-click deployment" and "efficiency settings." Nevertheless, the firm maintains a constructive outlook on AI applications that are driven by powerful foundational models and integrated into well-established ecosystems. Among numerous model providers, MiniMax stands out, having not only received a recommendation from OpenClaw founder Peter Steinberger but also ranking second on PinchBench (OpenClaw's large language model benchmark), just behind Gemini-3-flash. Morgan Stanley stated that OpenClaw is gaining rapid popularity in China, supported by domestic policy incentives and active productization efforts by internet and large language model (LLM) companies. The brokerage remains optimistic about companies with leading foundational models and ecosystem advantages. Morgan Stanley mentioned that for Tencent, a more proactive launch of products similar to OpenClaw could help counter recent bearish views labeling the company as an "AI laggard." The report highlighted that China is becoming one of the fastest-growing markets for OpenClaw adoption, driven by factors such as active participation from developer communities and demand for AI agents based on communication software, rapid productization by domestic cloud and foundational model providers, and policy tailwinds from China's broad "AI+" initiative, coupled with funding support from local governments. Morgan Stanley believes that the increasing popularity of OpenClaw further validates two major macro trends in China's AI sector: bottom-up adoption by individuals and small-to-medium enterprises (SMEs), and the application layer gradually becoming model-agnostic, allowing users to freely switch between leading domestic open-source models at very low token costs.