By
Tuhu Nugraha
Africa-Press – Mauritius. China’s recent strides in rural artificial intelligence (AI) adoption are offering powerful insights for countries across the Global South. In once-isolated agricultural regions, Chinese farmers are now accessing AI-driven insights for everything from pest control to crop selection. According to a report from the South China Morning Post (SCMP), these developments are part of broader efforts by Chinese tech giants and provincial governments to integrate AI into the agricultural economy as a means of reducing poverty and driving modernization. These innovations are not just about technology; they represent a broader vision of inclusive digital transformation that speaks directly to the needs of rural communities.
The foundation of this transformation lies in digital inclusion. China’s investment in rural connectivity—including 5G networks and smart platforms—has dramatically narrowed the urban-rural digital divide. SCMP highlights how targeted policies and infrastructure programs have accelerated this transition, particularly in underdeveloped inland provinces. For nations in the Global South, this highlights the urgency of building robust digital infrastructure in remote areas to unlock AI’s full potential. This is not merely a matter of connectivity, but a prerequisite for enabling equal access to knowledge, economic opportunities, and public services.
But access alone is not enough. China’s approach emphasizes empowering local communities by embedding AI into everyday agricultural practices. Farmers are now making more informed decisions about irrigation, fertilization, and harvesting based on AI recommendations. These tools enhance human judgment rather than replace it, making them particularly relevant for regions where traditional knowledge still plays a vital role.
A key element in China’s success has been the development of context-aware solutions, particularly through localized large language models (LLMs). The launch of DeepSeek, a domestic LLM, has enabled China to tailor AI systems to local dialects, cultural norms, and agricultural knowledge. This localization makes AI more intuitive for rural users, allowing technology to align with the way local communities think and solve problems. For the Global South, developing homegrown LLMs is not only a strategic necessity but also a cultural imperative—one that supports linguistic diversity and preserves indigenous wisdom.
For the Global South, replicating this model offers a tangible path toward poverty alleviation. By enabling smallholder farmers to increase productivity, reduce losses, and access timely market information, AI can directly improve household incomes and community resilience. Furthermore, localized AI applications can be extended to areas such as health, education, and disaster preparedness, multiplying their developmental impact.
Chinese Big Tech firms, such as Alibaba Group Holding and Tencent Holdings, have also played a key role in accelerating the proliferation of AI applications by developing user-friendly chatbots and AI tools tailored for broader use. Alibaba, entered into a strategic partnership with the Zhejiang provincial government to use AI technology as a means to reduce the rural-urban poverty gap. These public-private collaborations highlight the effectiveness of aligning technological advancement with social objectives, offering another model for the Global South to consider.
At the same time, recent research from Boston Consulting Group (BCG) reveals that a significant number of countries with the highest ChatGPT usage are from the Global South—including Indonesia, which ranks among the top globally. Approximately 50% of the top 21 countries identified in the study are developing nations, underscoring the rapidly growing interest and adoption of generative AI technologies in emerging markets. For instance, Indonesia ranks 6th globally, while other Global South countries like India (2nd), Brazil (7th), and the Philippines (11th) also feature prominently on the list. This surge points to a massive latent potential across these regions, driven by a digitally curious and young population. However, it also reveals a critical gap: the adoption is often fast but not well-structured or guided by long-term digital strategies. Without proper direction and investment in local capacity, this momentum risks becoming fragmented and dominated by foreign platforms, rather than enabling the creation of local value through context-aware AI solutions.
However, this vision is not without challenges. Infrastructure gaps remain a significant barrier, with many rural regions lacking reliable electricity, internet access, or affordable smart devices. In addition, the technological capacity to build and train LLMs is often limited due to resource constraints and a lack of research and development ecosystems. Human capital is another hurdle—many communities face shortages of skilled professionals in AI, data science, and digital pedagogy.
To overcome these challenges, a multi-pronged strategy is required. Governments must lead by investing in infrastructure and enacting supportive policies, while forging partnerships with private sector innovators and academic institutions. Capacity-building initiatives must focus not only on training developers and engineers but also on equipping end-users with digital literacy. Regional collaboration can also play a role in pooling resources and developing shared AI assets, including multilingual LLMs tailored to regional contexts.
In addition, the Global South must proactively build partnerships with leading AI innovators such as DeepSeek, OpenAI, and Google. These collaborations can facilitate technology transfer, access to foundational models, and joint innovation programs, thereby accelerating the development of localized AI solutions. Establishing joint research centers and AI development hubs is equally critical, serving as platforms for co-creation, experimentation, and capacity building. These centers can also help ensure that Global South nations are not mere consumers of technology but active contributors to the global AI landscape.
Crucially, China’s progress has been driven by a collaborative ecosystem involving government bodies, tech companies, research institutions, and local cooperatives. This pentahelix model offers a blueprint for the Global South to accelerate inclusive AI adoption. By fostering cross-sector collaboration, countries can ensure that innovations are co-created with communities and are widely accessible.
Lastly, the human dimension of this transformation cannot be overlooked. China’s rural AI deployment includes robust training and digital literacy programs, ensuring that farmers are equipped to use the tools effectively. For the Global South, investing in education and capacity-building is essential to ensure that AI’s benefits are inclusive and sustainable.
Ultimately, the lesson from China is not to replicate its model, but to adapt its principles. By investing in digital infrastructure, developing localized AI models, and nurturing community-driven innovation, the Global South can harness AI not just for productivity but for resilience, equity, and cultural continuity. In doing so, AI becomes a transformative force not only for rural revitalization but for systemic poverty reduction and sustainable development.
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