China aims to reform the global agricultural system with agricultural practices supported by artificial intelligence (AI). At the 2025 Seed Congress held from March 20 to 23 in Sanya, Hainan Province, China has illustrated its vision for data-driven production with concrete examples such as AI-driven breeding, cloud-based farm monitoring systems, and robotic automation tools. Super crop programs carried out by Chinese Academy of Sciences (CAS) enable the development of new climate-resilient crops through the integration of biotechnology and artificial intelligence.[1] These developments illustrate that China is not only improving its domestic agricultural productivity but is also establishing a form of “smart agriculture diplomacy” directed at international cooperation.
In parallel with these technological advancements, the United States Department of Agriculture (USDA) released its 2025–2026 Artificial Intelligence Strategy. The strategy aims to guide the integration of AI into the agricultural sector based on principles of transparency, ethics, data security, and governance.[2] Thus, clear differences have emerged between China and the United States not only at the technological level, but also in terms of normative frameworks and diplomatic approaches.
China’s recently implemented hybrid seed production system allows the prediction of high-yield varieties through genetic analysis without the need for extensive field trials, thereby accelerating the production process.[3] Led by the China National Seed Group, this system has the potential to enhance global competitiveness, particularly in strategic crops such as hybrid rice. Meanwhile, the China-Israel joint-developed 5G-enabled agricultural robots in Fujian are equipped with AI-powered sensors capable of monitoring crop health 24/7, enabling real-time management of the production cycle. In Chengdu, a 20-story vertical farming facility provides a compelling example of the future of urban food production by enabling the harvest of crops like lettuce within just 35 days, even in limited urban spaces.
China’s 2024–2028 Smart Agriculture Action Plan envisions the integrated use of artificial intelligence, big data, and location-based technologies.[4] This initiative marks a new phase in China’s rural digitalization strategy. Notably, the large language model “Fengdeng” provides AI-based decision-making support to farmers on critical issues such as crop health, climate scenarios, and yield forecasting, thereby facilitating the proliferation of an information-driven agricultural production model.
In this transformation process, China’s objective is not limited to increasing agricultural production, but also includes becoming a technology-exporting power and a setter of digital norms. The expansion of AI-powered agricultural advisory systems—particularly across Africa, Southeast Asia, and Central Asia—suggests that China’s technology exports are likely to evolve into instruments of geopolitical influence.
On the opposing front, the USDA’s AI Strategy is primarily grounded in principles of ethics, accountability, and human-centeredness. Through the appointment of a Chief AI Officer (CAIO), the establishment of oversight mechanisms such as the Generative AI Review Board, and the development of an AI Lab infrastructure, the United States seeks to integrate AI practices with internal governance frameworks. This model carries the potential for greater alignment with multilateral international organizations such as the Food and Agriculture Organization (FAO).
As a result of these two approaches, a global competitive dynamic is expected to emerge between China’s production efficiency–focused “field dominance” and the United States’ transparency and ethics–based “norm leadership.” Some countries are likely to adopt the Chinese model to boost production, while others may lean towards the U.S. model prioritizing data security and governance. This scenario points to a multipolar order in agricultural technology.
In the next phase of agricultural policy, concepts such as “data sovereignty,” “algorithmic neutrality,” and “technology diplomacy” are likely to gain greater prominence. While China’s short-term production successes are evident, its leadership claim will be tested in the medium to long term by the explainability of AI systems, commercial compliance, and integration with international standards. In this context, China’s leadership will be shaped not only by technological advancement but also by the degree of cooperation and transparency.
All these developments will extend beyond the agricultural sector, shaping international governance norms for artificial intelligence. The balance emerging between China’s operational influence on the ground and the United States’ norm-setting power is likely to become more visible in multilateral platforms such as the FAO in the future. This dynamic will lead not only to technological cooperation but also to a redefinition of political positions.
Issues such as data security, ethical algorithms, and the traceability of AI tools are expected to become not only technical concerns but also geopolitical and diplomatic priorities. From national security to trade policies, these topics are likely to generate new points of contention in interstate relations. While the U.S. approach emphasizes open data, accountability, and multistakeholder governance principles, China’s model prioritizes practical outcomes such as efficiency, speed, and centralized control. This divergence has profound implications not only at the level of strategic implementation but also for global ethical standards and international technology norms. Therefore, the future of AI-driven agricultural policies between the U.S. and China should be understood not merely as a race for production efficiency but also as a normative struggle over values. In the long term, this divergence is expected to directly influence decision-making processes within multilateral organizations and the technology import preferences of developing countries.
China is likely to export its AI-powered agricultural technologies to an increasing number of countries in the coming years. The expansion of vertical farming facilities in major cities and the centralization of food supply chains are expected. Accelerated production of super crops and the commercialization of climate-resilient varieties are also anticipated. AI-based advisory systems are expected to guide farmers’ decisions based on data-driven insights. The adoption of these technologies in developing countries is highly probable.
In conclusion, China is likely to emerge not only as a producer but also as a norm-setting actor in this field. However, the sustainability of this leadership may be challenged if issues related to data transparency, algorithmic security, and international compliance persist. The normative competition between the U.S. and China is expected to extend into the realm of agricultural technologies. In the long term, this transformation is likely to impact a wide range of areas, from global food policies to production structures.
[1] “China’s AI-Powered Smart Agriculture Revolutionizing Crop Breeding”, Xinhua, https://english.news.cn/20250325/949db5e982624e1f8886f95e2ef60c3b/c.html, (Date Accessed: 10.05.2025).
[2] “FY 2025–2026 USDA Artificial Intelligence Strategy”, USDA, https://www.usda.gov/sites/default/files/documents/fy-2025-2026-usda-ai-strategy.pdf, (Date Accessed: 10.05.2025).
[3] “China Boosts AI-Based Crop Development Amid Global Food Security Concerns”, Global Times, https://www.globaltimes.cn/page/202503/1330818.shtml, (Date Accessed: 10.05.2025).
[4] “China Seeks to Boost Food Output with Five-Year Smart Farming Plan”, Reuters, https://www.reuters.com/markets/asia/china-seeks-boost-food-output-with-five-year-smart-farming-plan-2024-10-25, (Date Accessed: 10.05.2025).
