Why China Could Dominate The Future of AI

China may soon overtake the United States in the global race for AI dominance. While US firms spend billions building compute to power proprietary models that may never prove profitable, China has sought to innovate to reduce costs while integrating artificial intelligence into both daily life and the broader economy. 

In recent years, Beijing has shifted from playing catch-up to positioning itself as a global leader, not only of AI development but also in global governance and innovation. China’s AI philosophy is grounded in cost efficiency through energy abundance, open sourcing (to spur both adoption and adaption), and governance frameworks that encourage international co-operation.

Beijing’s 2017 New Generation Artificial Intelligence Development Plan clearly mapped out an ambition to take an international lead in AI while building an AI economy valued at $1.4 trillion by 2030. The strategy acknowledges that dominance in the sector will come down to four key pillars: data, energy availability, computing capacity, and skilled labour.

China already holds a clear advantages in three of these areas. Its massive population creates scale in data. A rapid rollout of renewables and nuclear have already made China the world’s largest electricity producer. And China’s highly skilled STEM workforce is already comparable with globe’s top talent.

The only constraint has been access to cutting edge semiconductors. But this may no longer be a problem. Beijing shocked the tech world by instructing Chinese tech companies not to buy Nvidia chips in 2025, which suggests China has enough domestic capacity to meet domestic demand without relying on unfriendly suppliers. This confidence is grounded in large scale investments in local advanced chip fabrication with reports suggesting that China can now produce indigenous 3nm chips of their own.

As the world’s largest producer of manufactured goods, this rapid ascent up the AI hardware value chain should come as no surprise. Domestic chip foundries are scaling output, wind and solar projects continue to expand by tens of gigawatts every year, and nuclear reactor approvals are multiplying. The result is lower power costs, greater infrastructure density, and a more viable environment for the development of large scale AI applications.

By contrast, Washington may be overly focussed on export controls in a bid to maintain primacy, prioritizing short-term advantages rather than building long-term structural capacity or shared growth models. As China enhances its self-sufficiency, this strategy could backfire.

The US simply doesn’t have enough electricity to compete with China over the long run, with new data centres pushing up power prices for households and plans to build modular nuclear reactors facing delays. This is already leading to brownouts in US cities as data centres spring up like mushrooms. At the same time, Chinese models have been optimised to use less power.   

China is planning for the future through a combination of state planning and market incentives. Data has been elevated to the status of the fifth factor of production alongside, capital, labour, land, and technology, in official government policy papers. This sees Beijing treating data as an economic asset to be developed in the public interest, which translates to more competition.

China’s focus on futuristic innovation is so forward thinking that Beijing even plans to launch supercomputers in space. Capable of performing at hundreds of terabytes per second, these orbital workstations intend to resolve one of the biggest challenges surrounding compute which is the extraordinary cost of cooling the servers.  

In the vacuum of space, temperatures approach absolute zero and heat dissipates naturally without the need for costly, energy intensive cooling systems. If successful the initiative could reshape the economics of hyper-scale AI infrastructure.

Taken together these developments suggest China has various cost and capacity advantages over its Western rivals. Beijing’s renewable energy and data strategy, orbital computing ideas, and an abundance of computer science graduates, are all converging on a trajectory towards dominance in the artificial intelligence domain.

That said, one of the focus areas for Beijing which gets much less attention is in the realm of international AI rulemaking and governance. China has invested heavily in promoting dialogue among developing countries about developing a legal framework for the deployment of AI.

This remains a concern for smaller countries who fear AI could be weaponized to sway election outcomes or undermine financial stability in their nations. As such, Beijing is advancing an AI strategy that extends beyond domestic capacity and includes shaping the rules of the game.

China’s Global AI Governance Initiative has already set out proposed principles for equitable access, data security, privacy protection, and an open-source ethos which intends to prevent concentration of control among a few states or private corporations.

This initiative has been followed up with action plans designed to improve interoperability and expand AI capacity across the Global South. Diplomatically the approach has been multilateral and persistent with a China-led resolution on AI cooperation passing the UN General Assembly with backing from over 140 countries.

China has used the World AI Conference and the Shanghai Declaration to advance the idea of a Global AI Cooperation Organisation headquartered in Shanghai. The goal is to bridge digital divides and set consensus-based rules. China has also launched the Group of Friends for International Cooperation on AI Capacity-Building with Zambia, to narrow the technology gap.

Chinese private enterprise has stepped up to support the government’s ambitions, with various Chinese models matching or exceeded the performance of Western systems with lower energy requirements and consequently lower costs. This has already undermined the rationale for US export restrictions which appear ineffectual in light of recent Chinese innovations.

China is treating artificial intelligence as a means of modernisation, with applications focused on improving educational outcomes and industrial efficiency. While US stock markets soar to new unsustainable heights, China’s factories are increasing output and citizens in rural areas are increasing their social mobility thanks to these people orientated applications.

The choice to open-source key models also sharply contrast with the proprietary approach of leading American firms, lowering costs and barriers for developers and strengthening China’s appeal to developing nations. This undermines efforts by US big tech hoping to monopolize the technology and lock in long-term profits.

Considering Microsoft and Nvidia jointly account for a greater share of the US equity market than any two companies in history, the development of local Chinese operating systems, such as Harmony OS, combined with on-going breakthroughs in semiconductor fabrication, pose a genuine threat to a dangerously overconcentrated US financial system.

So while Washington continues to prioritise technological dominance through restriction and exclusion, Beijing’s open-source collaboration is building credibility as an alternative centre of gravity in the AI landscape.

At the same time, China has structural advantages which allow it to compete with the United States in the deployment of artificial intelligence, including more electricity and data scientists, while Beijing strives to define the norms and standards that will govern the technology globally.