Recently, HTX Research, the research department under Huobi HTX, published the latest research report "From the Outbreak of OpenClaw, See How AI Begins to Compete for the Real Entry Point to Work", focusing on the rapidly rising open-source project OpenClaw, systematically analyzing the industry trend of AI evolving from a Q&A tool to a manageable execution layer, and delving into the product layout and differentiated competitive strategy of Huobi HTX in the AI direction.

The core issue of the report is, when AI no longer just "answers questions" and begins to "execute tasks," who will control the next stage of entry into work. Around this question, the research report analyzes from five dimensions: product form, market driving force, evolution of human-machine division of labor, opportunities and risks in the Chinese market.

The Emergence of the AI Execution Layer: From "Better at Chatting" to "Really Getting Things Done"

The reason OpenClaw has attracted wide market attention lies in its focus on execution capability rather than answer quality. It is defined as a personal AI assistant running on the user's own device, capable of receiving tasks through various messaging entries such as WhatsApp, Telegram, Slack, Lark, and Teams, and linking files, browsers, calendars, emails, and terminals to complete actions. The research report points out that it is not competing for a new chat interface, but for the execution entry in the AI era—humans are gradually stepping back to the position of defining goals and making key judgments, while part of the execution chain begins to be taken on by digital agents.

This shift is backed by five trends maturing simultaneously: model capabilities have reached a "usable stage," sufficient to support moderately complex multi-step tasks; the high-frequency characteristics of messaging entries allow AI to embed in existing work interfaces rather than requiring users to migrate; the open-source distribution mechanism enables projects to quickly break through the developer circle; the self-hosted model addresses concerns of data sovereignty; and the real need for small teams to "do more with fewer people" provides the most direct pull.

The Special Adaptability of the Chinese Market

The report particularly points out that the dissemination potential of OpenClaw in the Chinese market should not be underestimated. The real work of a large number of small and medium teams in China occurs between messaging-driven interfaces such as WeChat Work, Lark, and customer service backends, which are naturally suitable for the penetration of such execution layer tools. Shenzhen, Wuxi, and other places have already launched subsidies, office space, and entrepreneurial support policies around the OpenClaw ecosystem, linking it to the narrative of "one-person companies." High messaging density scenarios such as content teams, agency operations, investment research monitoring, and customer service diversion are considered the first directions to succeed.

Security and Governance: Three Thresholds from Hot Projects to Infrastructure

However, OpenClaw still needs to cross three thresholds to become infrastructure. The first is the security threshold—recently, there have been cases of malicious installation packages spread through forged GitHub repositories and search ads; secondly, there is the governance threshold, where enterprises need clear permission auditing, action playback, and manual approval mechanisms; thirdly, there is the template threshold, where a general platform lacking industry-level access templates will find it difficult to cross the gulf from "trial use" to "long-term use."

Huobi HTX's AI Pathway: From Model Aggregation to Platform-Level Service Entry

As a global cryptocurrency trading platform deeply engaged in the AI field, Huobi HTX's pathway in the AI direction complements the trend represented by OpenClaw. OpenClaw represents the direction of "AI as an execution layer," while Huobi HTX is promoting "AI as a platform service entry and ecological connector" for practical implementation.

The self-developed AINFT product launched within the Huobi HTX system aggregates mainstream large model capabilities, including OpenAI, Anthropic, and Google, allowing users to access different models through a single entry without switching between multiple platforms. In terms of login, AINFT adopts TronLink wallet signature, eliminating the need to bind phone numbers or credit cards, aligning closely with the habits of native crypto users. The payment mechanism adopts a "pay-as-you-go" strategy, breaking the monthly subscription logic traditional AI products follow, which better suits the characteristics of on-chain users who require frequent, small, and flexible usage.

This product design reflects that Huobi HTX’s understanding of AI has upgraded from "efficiency tool" to "platform capability extension"—in the future, users entering the platform may not only be for trading but also for using AI and intelligent services, thereby flowing back to trading and platform activities.

In terms of competitive strategy, against the backdrop of major trading platforms launching AI Skills, Huobi HTX has adopted a more focused differentiation strategy: HTX AI Skills first covers spot and contract trading execution and plans to supplement market analysis, market intelligence, and built-in AI assistant in the app, establishing a closed loop around four key areas: "trade execution, risk assessment, market intelligence, user entry." The report points out that the core of competitiveness does not lie in the number of Skills stacked up but in who can first integrate execution, risk, intelligence, and entry into a complete user experience.

The Track is Still Early, but the Direction is Clear

The evolution of AI from tool layer to execution layer is still in a very early stage, with security, governance, and ecological maturity still far from being in place. However, the outbreak of OpenClaw has already allowed the market to see more clearly that the next competition in AI may not only be a contest of parameters and answer quality but may extend to comprehensive aspects of entry control, permission governance, skill ecology, and organizational trust. Huobi HTX's proactive layout in this direction provides a noteworthy industry example of how a crypto platform can transform AI from an external capability to a self-operable, growth-oriented long-term asset.

About HTX Research

HTX Research is the exclusive research department under Huobi HTX, responsible for conducting in-depth analysis in a wide range of fields including cryptocurrency, blockchain technology, and emerging market trends, preparing comprehensive reports, and providing professional assessments. HTX Research is committed to offering data-driven insights and strategic foresight, playing a key role in shaping industry opinions and supporting informed decision-making in the digital asset space. With rigorous research methodologies and cutting-edge data analysis, HTX Research always stands at the forefront of innovation, leading the development of industry thought and facilitating deep understanding of the ever-changing market dynamics. Visit us.

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