China’s rise in artificial intelligence reflects the strength of its state-directed economic playbook, which mobilizes capital, talent, and local governments around national priorities. Unlike the US’ predominantly market-led model, China’s centralized political authority combined with decentralized economic competition enables rapid policy execution and industrial coordination. Though prone to inefficiencies, this system accelerates technology diffusion and supports long-term innovation. History and current AI initiatives show a consistent pattern: when Beijing defines a strategic goal, the entire ecosystem pivots to deliver. The result is a resilient model that has propelled China’s technological progress and is increasingly shaping global debates on industrial policy and innovation.

On October 12th, 2016, President Obama’s White House released a major plan to harness the promise of artificial intelligence (AI). The plan outlined policy opportunities presented by AI, regulatory challenges on the horizon, and long-term research and development objectives. Prepared at remarkable speed, the plan reflected a sense of urgency rarely seen in traditional policymaking—the product of a National Science and Technology Council (NSTC) subcomittee that had been formed less than six months earlier. Yet the report, America’s first comprehensive national plan for AI, was largely overlooked amid the distractions of a heated presidential race. 

This response couldn’t have been more different in China. In July 2017, the Chinese State Council released the “New Generation Intelligence Development Plan,” Beijing’s answer to the White House plan, setting the goal of becoming the world’s leader in AI by 2030. But unlike the lukewarm response in the US, China’s report generated shockwaves across its tech and policy circles, igniting a surge of interest in AI and a wave of national mobilization. Within a year, China’s AI startup funding surpassed that of the US, accounting for nearly half of global AI investment, while local governments from Beijing to Shenzhen rushed to publish their own AI development roadmaps. Since then, Beijing has followed up with explicit milestones for 2030 leadership, backed by massive investment funds, AI research institutes, and startup incubators, among many other measures to build an innovation ecosystem second to none.

How could the reactions have been so different? It wasn’t simply that the White House’s plan was drowned out by a presidential race. Rather, it spoke to a fundamental divergence in the economic playbooks between the US and China. 

Today, China is a leader in artificial intelligence in several fronts, from computer vision and speech recognition to logistics automation. National champions like Tencent, Baidu, Alibaba, and Huawei have come to embody a distinctly Chinese model of techno-industrial mobilization while Shenzhen, once a cluster of rural fishing villages, has transformed into a global innovation hub in less than half a century. 

For years, free market ideologues have forecast China’s peak and inevitable decline. Yet the country’s political economy has proven flexible, resilient, and most importantly, extraordinarily effective at channeling resources in service of China’s long-term national interests. In the emerging era of technological competition, it is China’s top-down, state-directed playbook that has arguably shown itself better organized for sustained innovation than the West. This is a lesson policymakers would be wise to take seriously.

A defining characteristic of China’s economic system is that when the state speaks, society listens. Throughout modern Chinese history, this pattern of mobilization in service of national goals has been a constant. In the 1950s and 1960s, the “Two Bombs, One Satellite” program transformed a technologically backward China into a nuclear and space power, mobilizing more than 20,000 scientists and engineers at secret research bases. The 1986 “863 Program” reorganized dozens of research institutes around strategic technologies like microelectronics and biotechnology, the 2006 15-year science and technology plan ​​launched a series of megaprojects to transform China into an “innovation-oriented” society, while “Made in China 2025” extended this tradition into advanced manufacturing. Across these efforts, the pattern is clear. When Beijing defines a strategic interest, the entire system pivots—redirecting talent, capital, and policy toward the technologies deemed vital for the nation’s success.

It’s important to recognize that this pattern is not limited to technology. The same playbook guided China’s poverty alleviation campaign, which enlisted millions of local officials and organizations to lift nearly 100 million people out of extreme poverty by 2020.

China’s current drive to lead in artificial intelligence and advanced technology bears striking similarities to the Space Race. Back then, the United States prevailed by mobilizing its entire innovation ecosystem, linking government, universities, and industry under the newly created NASA. Federal funding flowed into research labs and graduate programs, expanding the nation’s scientific talent pool and feeding breakthroughs into industrial partners like Boeing and Northrop Grumman. This open, networked model stood in contrast to the Soviet approach, where space research was confined to the closed institutes of the Academy of Sciences and tightly managed under state control.

How is it that an ostensibly rigid, authoritarian Chinese state is able to do this? To get a sense of how China has been able to do so well, one must take a closer look at what China’s economic system really is. Contrary to those who prescribe China as “communist” or “socialist,” the Chinese economy is among the most open markets in the world. After Chairman Mao’s death in 1976, a series of reforms would see China steadily embrace private property, open to foreign investment, and become a member of the World Trade Organization (WTO) in 2001. These reforms ultimately propelled China into the economic superpower it is today.

At the heart of these reforms is competition. A defining feature of China’s economic system is the centralization of political power coupled with economic decentralization. In China, everyday economic management is ultimately managed by local governments—or as Keyu Jin describes, the “mayor economy”, a system whereby local cadres strive to achieve performance targets upon which political promotion is heavily based. The primary yardstick has traditionally been economic growth, driving phenomena such as “GDP tournaments” and “GDP worship,” where regional ratings and rankings are widely discussed and circulated across national media.

Notably, these yardsticks change with the centrally set priorities of a particular period. Where innovation has come to the fore as a defining priority of the AI race in recent years, local officials have been ready to shift resources and incentivize, by any means necessary, local innovation via a range of policy incentives. In June 2025, the city of Hangzhou unveiled a comprehensive AI development plan that includes building a 100 billion yuan (US$13.9 billion) AI industry fund, rolling out a 10 billion yuan computing power subsidy program, and offering grants of up to tens of millions of yuan to projects that support core AI technology and model development as part of its push to become a national AI innovation hub.

This system stands in contrast to the former Soviet Union, which had both a high degree of political and economic centralization. It also differs from federalism seen in the United States, where subnational governments face tighter fiscal and legal constraints, rely more heavily on market mechanisms and private capital, and lack the same latitude to rapidly mobilize large-scale industrial policy. In China, where local officials directly control vast resources and have the strong support of the state-owned banks, they can be far more effective. 

Given the scale and speed at which such resources are directed, there are bound to be inefficiencies. Such misallocation was evident in the case of overinvestments into real estate which led to the formation of “ghost cities” and developer defaults. But in the case of innovation, the process can be, as Kai-Fu Lee describes, both “highly inefficient and extraordinarily effective,” where overpaying in the short-term may be the right choice given the long-term upside is so large. In innovation-driven sectors, returns are inherently skewed: a single breakout success can justify dozens of failed or inefficient bets. China’s system may generate pockets of local misallocation, but at the national level it can still deliver outsized payoffs when those experiments produce transformative AI champions—as seen with DeepSeek. 

Ultimately, the contrast between the United States and China reflects two different but internally-coherent models of AI development. The US ecosystem, anchored in private-sector leadership, has excelled at frontier innovation by building a risk-tolerant, startup-driven culture that has produced global leaders such as Nvidia, Anthropic, and OpenAI, with government support prioritizing regulatory easing and infrastructure enablement. China’s system, by contrast, relies on the large-scale mobilization of capital resources across the entire AI stack—from compute and infrastructure to applications and deployment—coordinated through the state and local governments. This approach is often less efficient and prone to misallocation, but those inefficiencies are, in many ways, an accepted cost of competing at scale. The Chinese state’s willingness to deploy capital and incentives rapidly has driven much higher rates of AI diffusion across the real economy, embedding AI into everything from manufacturing to public services. And even as China continues to lag at the frontier of model development, its steady narrowing of the gap suggests that this state coordination is not only effective in accelerating practical adoption, but increasingly capable of supporting advances in core research as well.

In the book Why Nations Fail, Nobel laureates Daron Acemoglu and James Robinson argue that nations dominated by small political elites tend to build institutions that enrich the few while stifling innovation. On paper, China arguably fits the mold. In reality, its ability to generate innovation and growth tells a different story. China’s state-driven economic playbook has proven to be a powerful engine for the development and adoption of new technologies. While it diverges sharply from Western, market-led approaches, it confers a clear structural advantage in mobilizing capital, coordinating resources, and driving rapid adoption across the real economy. Notably, Washington has increasingly acknowledged this reality and begun borrowing selectively from China’s playbook, evidenced by its renewed embrace of industrial policy through the CHIPS and Science Act and unprecedented state involvement in firms such as Intel.

Predictions that China has reached its peak have surfaced for more than a decade, yet they have been repeatedly overtaken by the state’s demonstrated capacity to course-correct and concentrate resources with speed and scale. What was once dismissed as rigid or unsustainable now appears increasingly resilient and adaptive, offering important lessons for how we understand markets and economic systems beyond conventional free-market assumptions.

Image credits: Photo by __ drz __ on Unsplash

The author has requested to remain anonymous.