By Garbo Tian

A single person, a laptop, and a handful of AI tools are now often portrayed as enough to start a company. Over the past six months, the “one-person company” model—lightweight, low-cost, and highly flexible—has surged in popularity. Yet a field investigation by Beijing Evening News suggests a more grounded reality: despite its advantages in cost efficiency, speed, and decision-making, OPCs still run into the same structural bottlenecks as traditional startups—business model validation, customer acquisition, cost control, and profitability.

1. The Rise of the One-Person Company

A One-Person Company (OPC) refers to a founder-centric business structure in which an individual, supported by digital tools and external collaboration networks, operates independently or with a micro-team of no more than 10 people to complete value creation, delivery, and monetization.

According to the China OPC Development Trend Report (2025–2030), newly registered OPCs in China reached 2.86 million in the first half of 2025, up 47% year-on-year. Total OPC registrations have now surpassed 16 million nationwide.

Compared with traditional small businesses that rely on defined organizational hierarchies and centralized office environments, OPCs operate on a fundamentally different rhythm.

“I just came today because of the meeting. Usually I don’t come in,” said 42-year-old entrepreneur Liang Weiyin, who recently signed a lease in Zhongguancun AI Beiwai Community, located in Beijing’s northwestern fifth-ring area.

His setup reflects the OPC model: no fixed cubicles, flexible use of shared desks and meeting rooms, and fully demand-based workspace allocation. His team has three people—two based in Beijing and one domain expert overseas—coordinating primarily through cloud-based workflows.

While early-stage costs are significantly lower than traditional startups, Liang emphasizes that the underlying logic remains unchanged.

“The product I’m building is an AI-driven computational medicine data analytics system. The technical framework is already in place, with offline deployment and data security as key advantages,” he said.

However, the company has yet to generate revenue or secure commercial orders. The biggest concern is a mismatch between user demand and product design assumptions.

“AI is just a tool for efficiency. It doesn’t let you skip the core steps of entrepreneurship,” he added. The next stage, he said, is to rely on community-based resources and real user feedback to close that gap.

At 9 a.m., another founder, a post-90s entrepreneur surnamed Tang, arrives at work. She uses an AI system to track ongoing tasks while coordinating product communications with her team.

“In the past, you needed a dedicated marketing team. Now one person can handle it,” she said.

With a background in clinical medicine, Tang and her co-founder have built an AI + healthcare digital project using large-model technology. Repetitive tasks such as medical data entry and cross-hospital data aggregation are fully handled by AI, eliminating the need for large foundational data teams common in traditional health-tech firms.

After nine months, she has moved beyond the pure solo mode and begun building an offline team.

Compared with traditional companies, she said OPCs offer lower operating costs, shorter decision chains, and faster iteration cycles. But the downside is equally clear: risk is no longer distributed across a team.

“In traditional companies, risk and pressure are shared. In OPCs, the burden is concentrated on one person,” she said.

2. The Real Bottlenecks OPCs Must Break Through

Many assume OPCs can simply rely on AI tools to launch low-cost businesses and generate profits quickly. Field reporting suggests otherwise: the operational friction is far greater than commonly assumed.

In October 2025, post-80s entrepreneur Wang Yanxiang began his OPC venture, targeting the public welfare and nonprofit sector. He provides end-to-end services for civil nonprofit organizations, charities, and foundations.

His work covers the full lifecycle of offline public welfare events, along with AI-assisted online fundraising across platforms, supported by short-form video and multimedia outreach.

Unlike traditional small firms, his entire operation is handled personally.

To outsiders, OPCs appear to eliminate payroll costs and management overhead, leaving ample room for profit. Wang disagrees.

The first structural constraint, he argues, is the lack of “all-round capability.”

In his experience, capability fragmentation is widespread across industries. Some understand project opportunities but cannot handle client acquisition; others can sell but cannot implement AI tools.

OPC founders must break these silos—combining project planning, business negotiation, AI-driven content production, fundraising operations, and even basic accounting and tax filing.

“The hardest part isn’t learning one skill—it’s embedding AI tools into every operational workflow: fundraising, coordination, communication, compliance. I spent a long time just deploying and training my systems,” he said.

Customer acquisition is the second barrier.

Without brand recognition, OPCs rely heavily on personal networks. Wang’s current clients come mainly from prior relationships in the public welfare sector. Conversion of unfamiliar clients remains low.

More structurally, mid-to-large nonprofits and foundations tend to prefer service providers of similar scale. OPCs are often excluded at the selection stage.

AI tools also introduce hidden costs that compress margins.

The idea of “zero-cost AI entrepreneurship,” Wang said, is misleading. While basic AI tools for copywriting or image generation may be free, industry-specific customization is not.

Non-technical founders cannot easily deploy or fine-tune systems independently. For complex scenarios—such as large-scale fundraising or multi-channel outreach—AI model usage and private deployment consume substantial token-based costs, which can exceed what OPC operators can sustainably bear over time.

3. The “Core Lever” Required for Survival

Alongside OPC communities, a small number of niche OPC incubators have emerged.

In an office building near Zhonghe Street in Beijing’s Yizhuang district, one informal OPC incubator operates without formal recruitment messaging. It simply provides open desks and free meeting room bookings.

Zhu Guanlin

Founder Zhu Guanlin describes three types of users: temporary small-business operators, job seekers preparing for interviews, and the largest group—solo OPC founders.

Some desks remain empty. Zhu notes that many founders enter the space driven by the trend rather than a working business logic. They understand AI tools and “digital employees,” but skip core steps such as market validation and customer acquisition strategy.

One visitor had built several small AI tools and planned to sell them to other OPC founders via community channels. Zhu points out that similar tools already exist widely in the market.

The root issue, he argues, is a lack of competitive analysis and real user research.

From observable cases, OPCs that survive tend to rely on prior industry experience.

Zhu identifies two patterns: cross-border e-commerce operators who use AI to automate repetitive workflows while retaining stable customer bases; and AIGC creators who leverage strong content production skills to secure commercial orders from long-form video platforms.

A common misconception, he says, is that AI itself can generate business opportunities from scratch.

In reality, surviving OPCs already possess either customers, distribution channels, or industry expertise. AI tools primarily amplify existing capabilities or fill non-core gaps. They do not replace the underlying logic of entrepreneurship.

As Wang Yanxiang puts it, sustainable OPC operators are those who deeply specialize in a vertical sector and successfully integrate AI into operational workflows.

Tang adds that founders should not enter the space simply because of subsidies or AI tool hype. Instead, they must anchor their efforts in real industry pain points and personal positioning.

Among her peers, she has seen founders stall due to lack of viable operations, while others gradually regain momentum after recalibrating both strategy and technical approach.

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