Last year, technology journalist Raffaele Huang reported, “China’s ambition to turn its open-source artificial-intelligence models into a global standard has jolted American companies and policymakers, who fear U.S. models could be eclipsed and are mobilizing their responses to the threat.”[1] Open-source models lie at the heart of the Chinese strategy. Huang noted, “The models all have versions that are free for users to download and modify. This approach, commonly referred to as open source or open weight, is driving global adoption of Chinese AI technology. American companies that have kept their models proprietary are feeling the pressure.” One of Huang’s most important points was noting the likelihood that a few companies would eventually control the market. He explained, “The history of technology offers many examples where a welter of competitors in an industry’s infancy eventually evolved into a monopoly or oligopoly of a few players.” The likely winners reside in China and the United States — and China is quickly gaining the edge.

The Rise of Chinese Artificial Intelligence

Although charges of intellectual property theft had been made against Chinese AI firms, the rapid rise of Chinese AI models is also the result of an extraordinary push to educate China’s smartest young people. Technology journalist Zijing Wu reports, “For decades, genius classes have been turning out the leading lights of China’s science and technology sectors. It is hard to overstate how essential they have been to the development of the companies now challenging US tech dominance, especially in AI, robotics, and advanced manufacturing.”[2] When some of the world’s smartest people offer the results of their genius free — or for a very low cost — to the rest of the globe, the AI landscape begins to shift dramatically.

Technology journalist Caiwei Chen explains, “Chinese companies have repeatedly delivered AI models that match the performance of leading Western models at a fraction of the cost. … A recent MIT study found that Chinese open-source models have surpassed US models in total downloads. For developers and builders worldwide, access to near-frontier AI capabilities has never been this broad or this affordable.”[3] She adds, “These models differ in a crucial way from most US models like ChatGPT or Claude, which you pay to access and can’t inspect. The Chinese companies publish their models’ weights — numerical values that get set when a model is trained — so anyone can download, run, study, and modify them. If these open-source AI models keep getting better, they will not just offer the cheapest options for people who want access to frontier AI capabilities; they will change where innovation happens and who sets the standards.” That’s a big deal.

Futurist Mark van Rijmenam insists, “The lazy story is ‘China is catching up.’ The real story is more specific and more consequential: China is driving capability up while pushing cost down, fast enough that parity is already visible in key tasks, and in some niches (especially code and agentic workflows) the capability, cost equation now favors China. Leaders keep misreading this as a future problem. It’s a present operating reality. The ‘China is behind’ narrative is dead.”[4] That conclusion is being reached by numerous experts. Researcher and journalist John Leonard reports, “Some observers believe that China is taking the lead in AI, thanks to an open source AI strategy it has pursued over the last eight years. This has seen a steady stream of breakthrough models — such as DeepSeek, Qwen and Kimi — with open weights, little or no restriction on usage, and heavily reduced costs to the end user. ‘China now leads open source AI,’ says a new report by OpenUK, pointing to distillation techniques, government support, engineering skills and the rapid iteration of open models which together are fueling the breakneck pace of innovation.”[5]

As noted above, creating a standard used by most of the world is a big deal. And that is exactly what China is trying to accomplish. Patrick Childress, a partner at the law firm Holland & Knight and former assistant general counsel in the U.S. trade representative’s office, explains, “In Beijing, the focus is clearly on building mass-market AI that most people use. China has already employed this strategy to great effect in global trade. It doesn’t need to invent or manufacture the best products in the world to dominate trade in key industries. It wins by building ‘good enough’ products at massive scale and exporting those goods around the globe at low prices.”[6] In the race for AI dominance, Childress asserts, “If history is any guide, China is after market dominance, not technological supremacy.”

Childress predicts China will follow the strategy it has used in other areas. He writes, “First, China will control its own AI inputs by building Chinese compute capacity, hoarding training data and walling off a domestic talent pipeline. Second, it will grow its AI companies through massive state subsidies. And third, it will offer cheap prices to cost-sensitive customers as it pushes its ‘good enough’ AI models into global markets. The strategy is already emerging. … Once all AI models are adequate for most tasks, price becomes the differentiator. And no one competes on price like China.”

The Chinese Cost

Tal Feldman, a strategist at MP Materials, observes, “Whoever supplies the world’s A.I. will shape how the world thinks. As these models get smarter and more autonomous, we are outsourcing more and more thinking to them.”[7] He adds, “That ‘cognitive offloading’ must not go to models that were designed to promote a foreign government, no matter how inexpensive they are.” According to Feldman, “[Chinese] models are not as innocent as many people believe.” Why? He explains, “Chinese law … dictates what A.I. can say. ... By law, the models are prohibited from ‘harming the nation’s image’ or doing anything that might cause ‘separatism’ or undermine China’s ‘social stability.’ ... These products must promote the interests of the Chinese government. Propaganda and false claims are baked into them. So, the problem is less that these models are made in China than that they are made for China.”

Yaqiu Wang, a Chinese human rights researcher and fellow at the University of Pennsylvania’s Penn Project on the Future of U.S.-China relations, agrees that is a problem. She writes, “Most tech analysts are aware that Chinese models have Chinese Communist Party controls built into them, but the problem is often understood too narrowly. Many assume that these models simply refuse to answer politically sensitive questions or parrot the party line on topics such as Taiwan, the Tiananmen Square massacre and Chinese leader Xi Jinping. That is certainly part of the problem.”[8] So what’s the rest of the problem? According to Wang, “Non-Chinese developers are not immune to Chinese influence, they can be pressured, incentivized or regulated to audit their training data, test for political biases and reduce the effects of CCP information manipulation. … Granted, Beijing is unlikely to exercise the same degree of control over foreign audiences. But if its success inside China is any indication, we should not underestimate its ability to shape the global information environment — and over time, what people know and believe.”

Some observers aren’t as concerned about China’s potential to brainwash people as they are about China’s efforts to monopolize national and corporate technology infrastructure. In this area, China has played the long game — an it’s now paying off, especially in the developing world. Journalists Paul Mozur, Adam Satariano, and Aaron Krolik report, “For two decades, Chinese firms have wired Africa’s telecommunications networks and paved its roads. M-Pesa, Kenya’s celebrated mobile-money system, runs on Huawei technology. These tech ties gave China a foothold in the continent, which it is using to sell A.I.”[9]

Concluding Thoughts

The most important historical lesson to learn in the area of technology is: Companies that control the standards rule the market. Sharon Gai, an AI transformation strategist, keynote speaker, and former Alibaba executive, observes, “The prevailing narrative in boardrooms from London to New York was simple — China copies, the West innovates. That assumption was already wrong then. Today, it is dangerously outdated.”[10] More importantly, she notes, China’s strategy to achieve AI dominance is misunderstood. She explains, “The most persistent misunderstanding is that China’s AI strategy is about replicating what Silicon Valley has built. In reality, China’s approach to AI is architecturally different. Where Western tech companies have largely pursued AI as a product category — chatbots, copilots, and standalone tools that can be sold to enterprises — China has treated AI as infrastructure: a utility layer woven into the fabric of commerce, logistics, government services, and daily life.”

Dewardric McNeal, managing director and senior policy analyst at Longview Global, bluntly states, “[China is in a] race to ‘addict’ the rest of world to a tech stack. … But increasingly, it is not clear that the American stack is the one.”[11] If China succeeds in addicting the developing world to Chinese technology and infrastructure, it is likely to win the AI race for much of the world. The consequences could be dire.

Footnotes

[1] Raffaele Huang, “China’s Lead in Open-Source AI Jolts Washington and Silicon Valley,” The Wall Street Journal, 12 August 2025.

[2] Zijing Wu, “China’s genius plan to win the AI race is already paying off,” Financial Times, 31 January 2026.

[3] Caiwei Chen, “What’s next for Chinese open-source AI,” MIT Technology Review, 12 February 2026.

[4] Mark van Rijmenam, “China's AI Wave Forces the West to Wake Up,” Synthetic Minds Newsletter, 16 February 2026.

[5] John Leonard, “Why China is overtaking the US as open AI leader – Asian Tech Roundup,” Computing, 24 July 2026.

[6] Patrick Childress, “How China can corner the AI market with inferior technology,” The Washington Post, 5 August 2026.

[7] Tal Feldman, “The Hidden Cost of China’s Free A.I.,” The New York Times, 29 July 2026.

[8] Yaqiu Wang, “The Global Danger of China’s State-Controlled AI Models,” World Politics Review, 31 July 2026.

[9] Paul Mozur, Adam Satariano, and Aaron Krolik, “China’s A.I. Is Surging Across Africa. That Should Worry Silicon Valley.” The New York Times, 5 August 2026.

[10] Sharon Gai, “What Western companies misunderstand about China’s AI strategy,” Computer Weekly, 27 February 2026.

[11] Dewardric L. McNeal, “Op-ed: The U.S. lead over China in AI is all but gone. We need a change in national strategy,” CNBC, 2 August 2026.