In Cambodia’s Takeo Province, shrimp farmers are adopting China-developed artificial intelligence (AI) technologies to enhance productivity and efficiency. Under the China-ASEAN Smart Farm Integrated Development Pilot Program, drones conduct automated feeding while real-time water-quality monitoring systems provide data to optimize farming conditions. These innovations have reportedly more than tripled the annual income per hectare for local shrimp farmers.

The application of AI in developing countries is gaining attention amid concerns about a widening technological divide between wealthy and lower-income nations. According to a World Bank report, low- and middle-income countries lag significantly behind high-income economies in both the number of AI systems deployed and computing capacity. The African Data Centres Association similarly notes that Africa accounts for less than 1 percent of global data center capacity, a disparity that could exacerbate existing development gaps without sustained international cooperation.

China positions its AI technologies as accessible alternatives to the high-cost, resource-intensive models prevalent in developed countries. Zheng Changzhong, professor at Fudan University, highlights that China’s approach focuses on low-cost, adaptable AI solutions tailored to the needs of developing economies. Such technologies are seen as a means to accelerate industrialization and digital transformation aligned with local conditions.

Examples of Chinese AI adoption in developing nations include Brazil, where the State Grid Corporation of China utilizes its Bright Power large model to support safer and more reliable power-grid maintenance in complex terrains such as rainforests and coastal mountains. In South Africa, an intelligent rail-monitoring system developed by Huawei integrates optical and AI-driven machine vision to detect risks and enhance railway safety and inspection efficiency.

Luigi Gambardella, president of the international digital association ChinaEU, underscores the significance of China’s deployment of open-weight, lower-cost AI models, noting their potential to foster local innovation in universities and industries. He adds that China’s extensive AI use across manufacturing, robotics, logistics, and energy sectors provides valuable insights into improving safety and productivity.

China’s expanding cooperation with countries in the Global South extends beyond industrial applications and includes projects aimed at addressing climate change, public health, and food security. For instance, the China Meteorological Administration’s MAZU system, an AI-powered meteorological early warning platform, has been implemented in several vulnerable developing countries, including Pakistan, Ethiopia, Mongolia, and Djibouti. The system helps these nations enhance their disaster preparedness and mitigate the socioeconomic impacts of extreme weather events.

At the 2026 World AI Conference (WAIC) and the High-Level Meeting on Global AI Governance held in Shanghai, China unveiled a new action plan to promote international AI cooperation. The plan advocates for increased access to high-quality data, inclusive intelligent computing services, broader sharing of open-source AI ecosystems, and joint development of AI governance frameworks. It also emphasizes advancing AI applications across industries and nurturing digital talent globally.

Industry experts praise China’s openness in AI development. Alex Zhavoronkov, co-founder and CEO of Insilico Medicine, described China as a leader in the AI revolution, with source models openly available worldwide and practical applications driving economic value.

Several developing nations have expressed interest in strengthening AI partnerships with China to harness emerging opportunities. Assel Zhanassova, deputy head of the Administration of the President of Kazakhstan, stated that collaboration with China is crucial given the country’s development of advanced technologies. As AI continues to reshape global industries, China's efforts appear poised to influence growth trajectories across many developing regions.