China is using the global AI race to make a broader argument about how the technology should be governed: advanced AI should not become the exclusive property of a handful of countries or companies. In a commentary published by People’s Daily around the 2026 World AI Conference (WAIC), Beijing positioned open-source models, international cooperation and human oversight as pillars of an alternative AI governance model—while highlighting China’s growing role in AI development.

The argument comes at a moment when artificial intelligence is becoming increasingly intertwined with national competitiveness.

The latest generation of large language models is demanding enormous amounts of computing power, capital and specialized hardware. At the same time, increasingly capable AI agents and reasoning systems are raising questions about safety, control and who should have access to advanced technology.

Against that backdrop, China is advancing a model that combines open-source AI development with stronger government-led governance and international cooperation.

The message was prominent at the opening of the 2026 World AI Conference and High-Level Meeting on Global AI Governance, where Chinese President Xi Jinping called for efforts to build what he described as a just and equitable global AI governance system.

The People’s Daily commentary frames the issue as a choice between two broad approaches. One treats advanced AI primarily as a strategic technology requiring tight control; the other emphasizes openness and broader access.

China’s position, according to the commentary, is that AI should remain people-centered and produce benefits beyond the countries and companies capable of developing frontier systems.

That argument is not purely philosophical. China is increasingly using its own AI ecosystem to demonstrate what open access could look like.

Open-source models become a strategic instrument

One of the examples highlighted is Kimi K3, described in the commentary as a 2.8-trillion-parameter open-source model and the world’s largest open-source model by parameter count.

China has become one of the most active sources of open-source large models, according to the article, which says cumulative downloads of Chinese open-source models have exceeded 10 billion.

The strategic significance goes beyond model rankings.

Open-source AI can reduce the barriers for developers, startups, researchers and companies that cannot afford to build frontier models themselves. It can also encourage local customization, allowing organizations to adapt models to different languages, industries and regulatory environments.

For Chinese technology companies, competitive open models provide another route into international markets at a time when access to advanced computing hardware remains geopolitically contested.

The approach contrasts with the increasingly closed model-development strategies pursued by some frontier AI companies in the United States, where model weights, training data and development infrastructure can remain closely controlled.

That does not make open source inherently safer. Open models can also make powerful capabilities easier to reproduce and potentially misuse. The policy question is therefore shifting from whether AI should be open to determining which components, capabilities and deployment environments should remain open.

China links openness with AI governance

China’s AI policy is not advocating unrestricted access.

The commentary emphasizes what it describes as secure, controllable and trustworthy AI. It points to the country’s Global AI Governance Initiative, AI safety governance frameworks and international AI ethics initiatives as mechanisms for managing risks.

That combination—open technology alongside centralized governance—is one of the most distinctive features of China’s AI policy position.

The country is seeking to encourage AI development while establishing rules around risk assessment, classification, ethics and deployment.

The article also invokes the precautionary principle, citing AI researcher and Turing Award laureate Yoshua Bengio on the need to prepare for possible risks as AI systems become more capable and autonomous.

For enterprise AI leaders, this tension is increasingly familiar. Organizations want models that are flexible and inexpensive to deploy, but they also need controls around privacy, security, model behavior and accountability.

The same challenge exists at a national level.

A new international AI organization

The most consequential institutional development highlighted by the commentary is the establishment of the World AI Cooperation Organization, which China says was created during the 2026 WAIC and High-Level Meeting on Global AI Governance with 38 founding countries.

According to the article, the organization is intended to promote inclusive AI development and follows the purposes and principles of the UN Charter.

If it develops into a meaningful multilateral institution, it could become another venue for negotiating international AI standards, capacity building and governance.

Its significance will depend on participation and practical authority. AI governance is already fragmented across organizations and national regulatory systems, including the United Nations, OECD, G7, European Union and other multilateral forums.

A new organization would therefore need to demonstrate that it can complement rather than simply duplicate existing institutions.

China is also presenting AI capacity building as part of its international strategy. The country says it will provide 5,000 AI training opportunities for developing countries over the next five years and establish international AI application cooperation centers involving ASEAN, the Arab League, African Union, CELAC, the Shanghai Cooperation Organization and BRICS countries.

That approach frames AI infrastructure and expertise as development resources rather than solely strategic assets.

AI becomes a tool of cultural diplomacy

The commentary goes beyond computing and governance to emphasize AI’s role in cross-cultural exchange.

Examples include the Cultural Interactions Engine, which aims to identify connections among cultural heritage sites, and multilingual AI systems designed to translate audiovisual content across more than 130 languages.

China also points to the use of the Qwen large language model during the Milan-Cortina 2026 Winter Olympics as an example of AI becoming part of international public experiences.

These examples support a broader argument: AI can be used to connect languages, cultures and institutions rather than simply automate commercial processes.

For AI developers, multilingual capability is becoming strategically important. The dominance of English-language data and models has created concerns that AI could reproduce the cultural assumptions of a relatively narrow set of societies.

Models that perform well across Asian, African, Middle Eastern and other languages could therefore become important infrastructure for countries seeking alternatives to Western-developed AI systems.

China’s AI strategy is becoming more international

The evolution of China’s AI sector is also tied to a larger industrial strategy.

The country is simultaneously pursuing domestic technological self-reliance, AI commercialization, open-source development and international partnerships. The People’s Daily commentary presents this as the next stage of China’s progression from technology follower to global competitor.

The strategy is particularly relevant as the AI industry expands beyond frontier model development.

The next phase of competition will involve AI chips, cloud infrastructure, foundation models, agents, robotics, industrial AI, data centers and application ecosystems. Companies such as NVIDIA, Microsoft, Google, Amazon and Meta are competing across different parts of that stack, while Chinese companies including Alibaba, DeepSeek, Moonshot AI and others are developing alternative models and platforms.

Open-source models could become an important competitive layer because they allow countries and companies to build applications without depending entirely on a single proprietary provider.

An alternative vision of the AI economy

China’s message is ultimately about more than AI models.

It is proposing a vision in which advanced artificial intelligence becomes a shared infrastructure for economic development, while governments retain a significant role in managing risks and setting rules.

Whether that model gains international acceptance remains uncertain.

The global AI ecosystem is already divided by technology restrictions, semiconductor supply chains, regulatory differences and competing geopolitical interests. Openness itself is also contested, particularly when the capabilities being shared can have security implications.

Still, China’s growing influence in open-source AI means its approach will be difficult for policymakers and enterprise technology leaders to ignore.

The central question is no longer simply who builds the most powerful model.

It is who controls AI infrastructure, who gets access to it, which rules govern its use and whether the technology develops as a concentrated strategic asset or a widely distributed platform.

China is making clear which side of that debate it wants to occupy.

Market Landscape

The global AI market is increasingly dividing into several competing layers: proprietary frontier models, open-weight models, sovereign AI infrastructure and specialized application platforms.

China’s open-source push is significant because it offers developers an alternative to proprietary ecosystems controlled by companies such as OpenAI, Google, Anthropic, Microsoft and Meta.

At the infrastructure level, however, access to advanced AI accelerators remains a critical constraint. The global AI market therefore cannot be understood through model capabilities alone; semiconductor availability, cloud infrastructure, data-center capacity and developer ecosystems are equally important.

The governance debate is evolving in parallel. The OECD, United Nations, European Union and national governments are developing frameworks addressing transparency, safety, accountability and responsible AI.

China’s proposed international cooperation structure represents an attempt to shape that conversation from a different institutional and geopolitical position.

The commercial implications are substantial. If open models continue improving, enterprises may gain more flexibility to deploy AI locally, fine-tune systems for specific applications and reduce dependence on individual model providers. For AI developers, it could also create a more fragmented but competitive global model market.

Top Insights

• China is positioning open-source AI as an alternative to concentrated frontier-model control, potentially giving startups, enterprises and developing economies broader access to advanced capabilities.
• The country is pairing open AI models with governance frameworks focused on safety, controllability, ethics and human oversight as AI systems become increasingly autonomous.
• China says 38 countries joined a new World AI Cooperation Organization, creating another potential forum for international AI standards, cooperation and capacity building.
• AI multilingual systems and cultural applications illustrate China’s effort to position artificial intelligence as infrastructure for international connectivity, translation and cultural exchange.
• For enterprises, China’s approach could accelerate competition among proprietary and open models while increasing the importance of sovereign AI infrastructure, governance and interoperability.

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