OpenClaw Explodes in Popularity, Experts Discuss Ideal Regulatory Boundaries

Artificial intelligence has never lacked hot topics, but few concepts have sparked such widespread pursuit—from tech geeks to industry players, and even local governments—like OpenClaw did at its launch in 2026.

This year, the government work report first proposed “creating a new form of intelligent economy” and made key deployments to promote “intelligent agents.” Is OpenClaw’s technological frenzy a coincidental echo of national strategy, or an inevitable intersection in the course of history? What pain points does it truly address?

To explore this, Hexun.com interviewed Liu Yong, director of the Zhongguancun Internet Finance Research Institute. He believes that the explosion of OpenClaw is essentially a high resonance between technological evolution and national strategy. It precisely targets the pain points of reducing costs and improving efficiency in the real economy, and also signals a clear shift of AI application focus from “decision support” to “autonomous execution.”

Liu Yong pointed out that OpenClaw not only understands instructions but can directly operate software, read and write files, and call APIs on a computer, achieving a qualitative leap from “dialogue response” to “end-to-end completion of complex tasks.” This ability to move from “thinking” to “executing” allows AI to truly permeate every detail of R&D, production, and office work, becoming as fundamental as water, electricity, and coal infrastructure. The open-source nature of OpenClaw also enables small and medium-sized enterprises and individual developers to have their own “digital employees,” embodying the inclusive nature of the “intelligent economy.”

Alongside the surging wave of technology, structural opportunities at the industry level have also become clear. Liu Yong believes that the popularization of intelligent agents will generate two major dividends: first, an exponential increase in token consumption and reasoning computing power demand, which will ignite markets for high-performance AI chips, cloud computing services, and computing power leasing; second, security risks associated with system-level permissions of intelligent agents will give rise to a large ecosystem for “security barriers,” covering permission management, behavior auditing, data encryption, and other specialized fields.

However, on the flip side, when this “digital workforce” is granted system-level permissions, will it become a double-edged sword threatening security?

In response to questions about how regulation can balance innovation and risk, Liu Yong believes that “the ideal regulatory framework should not be a ‘one-size-fits-all’ ban, but should resemble traffic rules—‘set signs and install guardrails.’” He even suggests that ordinary users “avoid deploying directly on main computers; instead, use backup machines or isolated cloud environments.”

Below is a summary of the dialogue:

Hexun: Many people are still unclear about the fundamental difference between intelligent agents and the large models we use daily.

Liu Yong: This is a very key concept. If large models are “smart brains,” then intelligent agents are “brains with hands and feet.”

Past applications of large models mostly stayed at the level of Q&A and text generation—“knowledge assistance.” The core of intelligent agents is “can see and do.” They possess autonomous planning, perception, decision-making, and execution capabilities. Take OpenClaw as an example: it not only understands your instructions but can directly operate software, read/write files, and call APIs, transforming from “dialogue response” to “end-to-end complex task completion.”

This shift from “thinking” to “executing” means AI will truly penetrate every detail of R&D, production, office work, and daily life, becoming as fundamental as water, electricity, and coal infrastructure.

Hexun: You mentioned that OpenClaw marks the beginning of a new era. What specific aspects of its core appeal stand out?

Liu Yong: The key lies in “autonomy” and “initiative.” Traditional AI tools require users to explicitly give each instruction, but intelligent agents like OpenClaw can, after receiving a macro goal, break down tasks, call tools, execute, and provide feedback independently.

This capability turns AI from a “chat tool” into a genuine “digital workforce.” Whether it’s automatically handling emails, coding, or market research, it can to some extent replace repetitive human labor, and even outperform humans in certain fields—working 24/7 without breaks. This is the fundamental reason it has rapidly moved from niche geek circles to mainstream awareness.

Hexun: The government work report this year first proposed “creating a new form of intelligent economy” and focused on promoting “intelligent agents.” Do you think OpenClaw’s emergence aligns with national strategic timing? What pain points does it address?

Liu Yong: The rise of OpenClaw is essentially a high resonance between technological progress and national strategy.

First, it responds to the call for “productivity upgrades.” In the context of rising manufacturing labor costs and underutilized traditional production lines, OpenClaw’s abilities—automatic monitoring, generating production plans, data processing—precisely target the pain points of reducing costs and improving efficiency in the real economy.

Second, it aligns with the direction of “technological equity.” Previously, AI systems capable of executing complex tasks were mostly accessible only to large corporations. OpenClaw, as an open-source project combined with cloud deployment templates, allows SMEs and individual developers to have their own “digital employees.” This embodies the inclusive nature of the “intelligent economy” and signals a clear shift of AI application focus from “decision support” to “autonomous execution.”

Hexun: We noticed that Shenzhen Longgang District issued the “Lobster Ten Rules.” How do you evaluate local governments’ competitive pursuit in the intelligent agent field?

Liu Yong: This is a very perceptive and forward-looking move. The proactive “battleship” approach reflects local governments’ determination and flexibility to develop new productive forces.

This policy not only lowers development barriers through subsidies but also aims to build a complete industrial ecosystem—providing free computing power, open public data, supporting hardware purchases, and encouraging technological export. Such comprehensive services can quickly attract talent and enterprises, creating industrial agglomeration effects. It sets a good example for other regions—future regional economic competition will be about not just attracting companies but also competing for technological ecosystems and innovation environments.

Hexun: As intelligent agents become more widespread, where do you see the major structural opportunities in the industry?

Liu Yong: There are mainly two major dividends:

First, infrastructure for computing power. Since intelligent agents require continuous model calls to perform complex tasks, the demand for token consumption and inference computing power will grow exponentially. This will trigger explosive growth in high-performance AI chips, cloud services, and computing power leasing markets.

Second, security and compliance ecosystems. Because intelligent agents have system-level permissions, the security risks are far greater than before. Therefore, building “security barriers” around intelligent agents—covering permission management, behavior auditing, data encryption, plugin review—will become a necessity. Those who can provide a secure, controllable environment for intelligent agents will occupy a crucial position in this wave.

Hexun: How should regulators balance innovation and risk regarding emerging technologies like OpenClaw?

Liu Yong: Currently, multiple authorities—including national regulators and industry associations—have issued risk alerts related to OpenClaw, covering cybersecurity, financial applications, and other core areas, reflecting a cautious approach that values both development and safety. I believe the ideal regulatory framework should not be a blanket ban but resemble traffic rules—“set signs and install guardrails.”

First, define safety bottom lines—such as standards for data privacy, algorithm transparency, and responsibility attribution. Second, promote industry standards and ethical norms, especially in permission control and plugin review. Lastly, regulation should maintain flexibility, allowing room for trial and error in technological innovation. The goal is not to stifle innovation but to guide technology along a correct and sustainable path.

Hexun: For ordinary users and enterprises caught up in the current “Lobster” craze, do you have specific advice?

Liu Yong: I recommend maintaining rationality, prioritizing “safety first, value-oriented.”

First, ensure security. Avoid deploying directly on main computers; use backup machines or isolated cloud environments. Strictly follow the “least privilege” principle; do not grant unnecessary system permissions. Be cautious with third-party plugins to prevent malicious code injection.

Second, clarify your purpose. Technology is a tool; the core is creating value. Whether individual or enterprise, think about how to use intelligent agents to solve real problems and improve efficiency, rather than blindly following trends or obsessing over the technology itself. It’s wise to wait and see or get on board—what matters is ensuring safety and making technology truly serve our work and life.