South-South cooperation provides avenues for countries to extract greater dividends from existing capabilities by pooling resources, sharing implementation lessons and building more context-appropriate AI systems.
The principle of “AI for the positive and for good” undergirds China’s AI+ International Cooperation Initiative, which was unveiled by the Ministry of Foreign Affairs of China last September, while the introduction of AI as a formal field of study is generally attributed to a conference held in the summer of 1956, at Dartmouth College in Hanover, New Hampshire.
1956 was also the year the world’s first transatlantic undersea telephone cable entered service, connecting Scotland and Newfoundland, Canada. You may also be interested to know that the Chinese Association of Automation was established in 1961. Automation was, and continues to be, an essential area of application for AI.
Today, AI is a global phenomenon. Narratives about AI abound, reflecting the diversity in different countries’ capacity in basic science, technological innovation, business application, regulation and expectations or anxieties about future prospects for AI development. It is possible to summarize the various views as four competing narratives:
1. AI enables and maintains an open and expanding pan-national network of factors of production. In science studies, AI is inherently global. In the social sciences, AI is empowering, but its impact on the pace and direction of change is not uniform. There are major digital gaps between countries and within societies.
2. AI innovation is like an arms race between competing nations. This interpretation is prevalent in public discussions and impacts policy discussions about international cooperation, although mainly among countries with peer-level capacities.
3. AI is an asset in a world market of competing institutions—universities, research labs, funding agencies and the like—and the focus is often on identifying leaders and followers.
4. AI is yet another manifestation of the center-periphery hierarchy in the world system. In this view, some countries are dominant, while others may have to settle for being low on the ladder of digital and associated technologies.
For all countries, AI is an evolutionary product of information and telecommunications technologies, enabling astonishing levels of automation in industrial and service industries.
The marketization of AI models comes in two modalities: closed source and open source. A model is “open” when most of the materials and processes used to create the model are published. When a model is “open weight,” its parameters can be downloaded, run locally, and modified. As such, for users, the difference is not just in the price but also the opportunity for customization. AI models by Chinese companies are open source and open-weight.
Let me try to contrast these models in plain language: With open-source models, you can deploy the model yourself, run it locally or choose a cheaper hosting provider. You do not have to be tied to one company’s pricing or mood. Users juggle in a triangle of choices: affordable, open and good enough. For closed-source models, that is almost impossible.
Still, for many users, especially those in developing countries, a prerequisite for getting on the ladder of AI services is to have in place the enabling infrastructure: a stable supply of quality electricity and locally hosted data centers that allow them to avoid having to compete for the same computing power that serves customers in other countries. For developing countries, the central question is no longer only how to expand digital access but how to turn that access into productive capacity, competitive firms, quality jobs and new trade opportunities.
China’s Belt and Road Initiative, formally launched in 2013, both endorses and promotes efforts to bring digital services to consumers in the Global South. Energy projects by Chinese companies positively contribute to Global South societies’ efforts to move up the energy ladder. Information and communications companies from China bring all devices, networking components, applications and systems that allow people and organizations to interact in the digital world. In the ICT sector, a core feature of Chinese business activities in the Global South is that they offer devices and services at affordable prices to their end users.
With the globalization of the digital economy, cross-border e-commerce has emerged as a new engine for international trade growth and a pathway for developing countries to integrate into global value chains and achieve inclusive development, including for women and minority groups. South-South cooperation, a key mechanism for China and developing countries to pursue collective self-reliance and share the benefits of development, is embracing new opportunities in the digital transformation within the framework of the Global Development Initiative.
The BRI now features all-of-government and all-industry projects grouped into three “Silk Roads”: digital, health and space.
Yes, the space industry is relevant to the pursuit of AI development. For China and the Global South, satellite technologies and services play a vital role in sectors such as agriculture, disaster management and climate monitoring. Despite limited involvement in early space exploration, Global South countries have made significant contributions to space law, advocating for equitable access and the peaceful use of outer space. Many emerging space nations have highly skilled experts in the field of space governance and technology.
A core component of China’s offer to interact with Global South countries is to address the latter’s limited resources to effectively access this expertise available in China. Further cooperation between China and the Global South can, and indeed should, begin with technical training in the dissemination and application of satellite data.
I would be remiss not to mention security concerns associated with the global AI ecosystem. The frameworks being built to evaluate AI systems, the standards being set to govern them and the institutions being created to oversee them have largely been designed for a small set of high-income countries. The Global South—with its diverse languages, institutions and communities— continues to sit at the margins of the larger AI safety discourse.
I proceed from the recognition that moving from insecurity to security is akin to moving from disease to health. In other words, security is relative and relational. There is every reason for Chinese and Global South researchers and entities to approach the issue as one of safety rather than security. Concerns in some parts of the Global South about reliance on foreign-supplied infrastructure, cloud platforms and proprietary models presents a strategic challenge that needs to be put in context: From land stations of undersea cable, to satellite receiving terminals and data centers, every country, large or small, rich or poor, has total sovereign ownership and control. Moreover, AI investments from abroad have to abide by the regulatory rules of a host country in order to function. As such, a Global South country has agency in AI and AI-related foreign investment.
It would be a mistake not to move away from abstract risk taxonomies. If anything, South-South cooperation provides avenues for countries to extract greater dividends from existing capabilities by pooling resources, sharing implementation lessons and building more context-appropriate AI systems.
Chinese President Xi Jinping put it this way at the 2026 World AI Conference and High-Level Meeting on Global AI Governance in Shanghai:
“In China’s view, all countries should take a people-centered approach and develop AI for the positive and for good. We should ensure that AI is a key driver of shared prosperity and common security. We should join hands to build a just and equitable system for global AI governance.”
