For three consecutive years, the Government Work Report has emphasized the "AI+" initiative. This year marks the first inclusion of the "intelligent economy" concept, signaling a clear policy evolution. This progression indicates that China's artificial intelligence sector is transitioning from a phase focused on technological R&D and application scenarios to a new stage of deep industrial integration and comprehensive economic empowerment.
At the start of 2026, new business forms like the One-Person Company (OPC) model, representative of the intelligent economy, are beginning to emerge. Leveraging AI agents such as OpenClaw and Miaoda, a wave of entrepreneurs is becoming "super individuals." These solo founders are building commercial-grade application platforms in vertical sectors like AI web series, smartwatches, AI-powered HR solutions, and corporate intelligent sites, pioneering a new entrepreneurial paradigm of "single-person drive with AI collaboration."
AI empowerment is reshaping the startup ecosystem, enabling individuals to achieve what once required teams. A national political committee member and researcher noted that learning to use AI agent tools will be essential for everyone. The term "raising lobsters" has become popular in AI circles, referring to the long-term training of the OpenClaw agent, symbolized by a red lobster icon. This process involves accumulating memory through sustained interaction, gradually cultivating the agent into a super assistant capable of time awareness, email management, and content creation, which can then be used to develop personalized, economically valuable applications.
The emergence of AI agents has democratized application development, allowing individuals without coding skills to create functional applications quickly. This has given rise to the potent OPC model, a highly dynamic component of the intelligent economy. This shift represents not just a minor adaptation by individuals to technological change but a profound reflection of national strategy and epochal transformation at a micro level. One expert described artificial general intelligence (AGI) as a second leap in Earth's intelligence.
Data illustrates the depth of this change: tasks previously requiring a team of ten people working for a week can now be completed in days or even hours with the aid of always-on AI agents. Furthermore, AI applications can optimize themselves in real-time based on user feedback, leading to higher efficiency and lower costs. The OPC trend is seen not as a short-term boom but as a long-term shift in the structure of social labor division and economic activity units.
Confidence in the OPC sector is high, with predictions of numerous OPC unicorns emerging within five years. AI significantly lowers barriers to entry and the cost of experimentation, unleashing individual innovative potential. OPCs are often adept at identifying common needs and pain points in niche markets, and their characteristics—being asset-light, fast-iterating, and deeply vertical—align perfectly with the logic of the digital economy. Young, motivated individuals are encouraged to explore viable, sustainable business models within the rapidly developing AI application field, using AI tools to efficiently realize ideas that previously required substantial investment.
The rise of OPCs is receiving positive responses at the policy level. Beijing recently launched an AI OPC service plan, establishing a cultivation system through measures like rent reduction and computing power support. Shenzhen aims to build over ten OPC communities and cultivate more than a thousand high-growth AI startups by 2027. Cities like Suzhou and Hangzhou are also actively building OPC entrepreneurial ecosystems, with many localities introducing supportive policies.
However, challenges remain for OPC development. As a novel company structure, OPCs face issues such as blurred lines between personal and company assets and unclear intellectual property ownership of AI-generated content. There is also an ecological challenge, as OPC founders often work in isolation, lacking a supportive community. Additionally, traditional financial institutions offer limited credit products tailored for these asset-light entities.
From a technical perspective, the profitability of an OPC is highly dependent on computing power and data. Currently, there is insufficient access to affordable computing power and high-quality open data for OPCs, which constrains AI model training and product iteration. To enable OPCs to advance rapidly and ensure the intelligent economy develops beneficially, safely, and fairly, a combination of policy measures is recommended. This includes issuing OPC compliance guidelines to clarify responsibilities regarding AI ethics and data usage, defining IP ownership, granting compliant OPCs tiered access to high-quality, anonymized datasets, and providing supporting affordable computing power. Financially, exploring ways to incorporate "digital assets"—such as code contributions, user growth, and open-source influence—into credit assessment systems could lead to tailor-made financial products, helping OPCs accelerate their growth in the new economic landscape.
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