Recently, HTX Research, the research arm of Huobi HTX, released its latest research report , "From the Explosion of OpenClaw, How AI Begins to Compete for the Real Entry Point of Work." The report systematically analyzes the industry trend of AI evolving from question-answering tools to managed execution layers, focusing on the rapidly rising open-source project OpenClaw. It also delves into Huobi HTX's product layout and differentiated competitive strategies in the field of AI.
The report's core theme is: when AI moves beyond simply "answering questions" and begins to "perform tasks," who will control the entry point to the next stage of work? The report analyzes this issue from five dimensions: product form, market drivers, the evolution of human-machine division of labor, and the opportunities and risk thresholds in the Chinese market.
The emergence of AI execution layers: from "better at chatting" to "actually doing things"
The reason OpenClaw has attracted widespread market attention is that it focuses not on the quality of responses, but on execution capabilities. It is defined as a personal AI assistant running on the user's own device, capable of receiving tasks through multiple messaging platforms such as WhatsApp, Telegram, Slack, Lark, and Teams, and completing actions in conjunction with files, browsers, calendars, emails, and other devices. Research reports point out that it is not competing for a new chat interface, but rather for the execution gateway in the AI era—humans are gradually retreating to the position of goal definition and key judgment, with digital agents beginning to handle part of the execution chain.
Behind this transformation, five trends matured simultaneously: model capabilities reached a "sufficient" stage, enough to support multi-step tasks of moderate complexity; the high-frequency nature of message entry points allowed AI to be embedded in existing work interfaces rather than requiring users to migrate; open-source distribution mechanisms enabled projects to quickly break through developer circles; the self-hosted model responded to concerns about data sovereignty; and the real need of small teams to "do more with fewer people" provided the most direct driving force.
Special Adaptability of the Chinese Market
The research report specifically points out that OpenClaw's potential for adoption in the Chinese market cannot be ignored. A large number of small and medium-sized teams in China actually work through message-driven interfaces such as WeChat Work, Lark, and customer service back-end systems, making them naturally suited for the penetration of these execution-level tools. Cities like Shenzhen and Wuxi have already launched subsidies, office space, and startup support policies around the OpenClaw ecosystem, linking it to the "one-person company" narrative. High-message-density scenarios such as content teams, agency operations, investment research monitoring, and customer service outsourcing are considered to be the first areas to successfully implement the technology.
Security and Governance: Three Thresholds from Hot Projects to Infrastructure
However, OpenClaw still needs to overcome three hurdles before it can become infrastructure. First is the security hurdle—recently there have been cases of malicious installation packages being spread through fake GitHub repositories and search ads; second is the governance hurdle—enterprises need clear permission auditing, action playback, and manual approval mechanisms; and third is the template hurdle—general platforms will find it difficult to cross the gap between "trying it out" and "long-term use" if they lack industry-level access templates.
Huobi HTX's AI Path: From Model Aggregation to Platform-Level Service Entry Point
As a global crypto trading platform deeply rooted in the field of AI, Huobi HTX's path in AI complements the trend represented by OpenClaw. OpenClaw represents the direction of "AI as the execution layer," while Huobi HTX is promoting the practical implementation of "AI as a platform service entry point and ecosystem connector."
Huobi HTX's self-developed AINFT product aggregates the capabilities of mainstream large-scale models from OpenAI, Anthropic, and Google. Users can access different models through a single entry point without switching between multiple platforms. For login, AINFT uses TronLink wallet signatures, eliminating the need to bind a mobile phone number or credit card, aligning with the habits of native crypto users. For payment, it adopts a "pay-as-you-go" mechanism, breaking away from the traditional monthly subscription logic of AI products and better suiting the high-frequency, small-amount, and flexible usage characteristics of on-chain users.
This product design reflects that Huobi HTX's understanding of AI has evolved from "efficiency tool" to "platform capability extension"—in the future, users will not necessarily enter the platform just for trading, but may also come to use AI and intelligent services, thus returning to trading and platform activities.
In terms of competitive strategy, amidst the current trend of mainstream trading platforms launching AI Skills, Huobi HTX has adopted a more focused and differentiated approach: HTX AI Skills initially covers spot and futures trading execution, with plans to subsequently supplement this with market analysis, market intelligence, and an in-app AI assistant, establishing a closed loop around four key aspects: "trade execution, risk assessment, market intelligence, and user access." The research report points out that the core of competitiveness lies not in the sheer number of skills, but in who is the first to connect execution, risk, intelligence, and access into a complete user experience.
The track is still in its early stages, but the direction is already clear.
The evolution of AI from the tool layer to the execution layer is still in its very early stages, with security, governance, and ecosystem maturity far from being achieved. However, the emergence of OpenClaw has made it clear to the market that the next stage of competition in AI may no longer be just a contest of parameters and response quality, but will extend to a comprehensive level encompassing access control, permission governance, skill ecosystems, and organizational trust. Huobi HTX's early deployment in this direction provides a noteworthy industry example of how crypto platforms can transform AI from an external capability into their own operable and scalable long-term assets.
About HTX Research
HTX Research is Huobi HTX 's dedicated research department, responsible for in-depth analysis, comprehensive reporting, and professional assessments across a wide range of areas including cryptocurrencies, blockchain technology, and emerging market trends. HTX Research is committed to providing data-driven insights and strategic foresight, playing a key role in shaping industry perspectives and supporting informed decision-making in the digital asset space. With rigorous research methodologies and cutting-edge data analysis, HTX Research consistently stays at the forefront of innovation, leading industry thought and fostering a deeper understanding of ever-changing market dynamics. Visit us .
If you would like to communicate further, please contact research@htx-inc.com
