China’s food security has long been a top priority for the government. As the country grapples with shifting geopolitical tensions, climate change, and domestic challenges, artificial intelligence (AI) holds the potential to reshape food security efforts and boost agricultural productivity.
China’s food security situation
Food security has long been a concern for the Chinese authorities. Amid changing geopolitical dynamics, climate change, trade tensions with the United States (U.S.)., and domestic challenges, China has prioritised food security. A key focus of this is boosting local agricultural production as reflected in a plethora of policies, plans, and targets at both national and provincial/local levels.
Despite efforts to increase local output, significant issues from limited arable land and water resource constraints to significant soil pollution make it an uphill battle. Adding to concerns, China’s food self-sufficiency ratio has plummeted, from 93.6 per cent in 2000 to 65.8 per cent in 2020. In 2004, China moved from being a net exporter to a net importer and is expected to remain one.
How AI could help
The benefits are significant. According to the International Food Policy Research Institute, AI could potentially increase farm productivity globally by as much as 67 percent by 2050 and decrease food prices by nearly 50 percent over the same period.
AI can help China tackle its agricultural challenges by enhancing agricultural efficiency and optimizing supply chains. Drones, satellites, and sensors enable real-time monitoring of crops, soil, and weather, while AI-driven disease and pest prediction slashes crop loss and boosts yields. Furthermore, AI helps streamline supply chains, improving storage and transportation efficiency to reduce food waste. Given that as much as 6 percent of China’s total food production is “lost” during household and warehouse storage, transport, and processing, there is a clear need for such technologies, demonstrating AI’s critical role in bridging gaps from farm to table.
Stronger utilisation of AI in food production aligns with the Chinese government’s broader strategy to become a global leader in artificial intelligence. As outlined in the 2017 New Generation AI Development Plan, China aims to lead in AI by 2030, with a focus on breakthroughs in AI infrastructure, applications, and industrial integration. This ambition is not limited to technology and infrastructure sectors but also extends to critical areas like agriculture, which is undergoing a significant transformation through digital tools.
Some steps have been taken to achieve this. At a national level, Beijing has introduced digitalization as a core strategy for agricultural modernization. Plans like the National Smart Agriculture Implementation Plan (2024-2028) and the 14th Five-Year Plan for Agricultural Modernization (2021-2025) emphasize the importance of using artificial intelligence, big data, and remote sensing technologies to improve farming efficiency and productivity. These efforts are central to China’s vision of modernizing agriculture through digital tools, ensuring the sector can meet future demands while improving overall productivity.
Efforts are undertaken at a local level too. In Hebei Province, an AI-powered online farming system “Xiongxiaonong”. Developed by the Agriculture and Rural Affairs Bureau of Xiong’an New Area and China Telecom, it is the country’s first agriculture-focused large AI model powered by DeepSeek and is tailored to Xiong’an’s agriculture specialty industries.
The model has proved effective. In just one month, the system helped the Yangque Lake Xili Agricultural Park optimize its tomato harvest by using AI to predict market prices, resulting in a nearly 3,000-yuan (US$420) income boost per mu for farmers.
Elsewhere, in Sichuan Province AI-driven robots integrated with DeepSeek-equipped high-definition cameras in smart greenhouses have revolutionized pest management. Sending real-time crop images from the cameras to the cloud for analysis has improved pest identification accuracy to over 80 percent. These successes demonstrate how AI technologies are driving efficiency and boosting productivity in agriculture.
Challenges
Challenges lie ahead. In addition to persisting concerns about privacy and ethics, other concerns must be addressed.
Notably, China’s agricultural model, primarily based on small family farms scattered across the country, faces significant obstacles to modernization, particularly in adopting agricultural technologies and standardizing practices. These issues hinder productivity and slow the advancement of technology and biotechnology needed to meet growing food demands. The transition from this fragmented farming structure to a more efficient, technology-driven sector is still in its early stages and faces resistance, particularly in rural areas.
Some initiatives like the National Agricultural Technology and Education Cloud Platform aim to address these gaps through online training. But stronger efforts are required to drive broader agricultural innovation to ensure long-term food security.
Financial constraints also pose a significant barrier. Smallholder farmers, who manage more than 70 percent of China’s agricultural land, often struggle with limited access to credit. Studies show that 18.87 percent of family farms face a funding gap, and 26.20 percent of those with formal credit still cannot fully cover their needs, further deterring investments in agricultural technologies.
On a national scale, also, local governments are trapped in a vicious cycle of high debt and dwindling revenues due in part to the real estate crisis which has undermined income from land sales. While the central government introduced a 10 trillion (US$1.4 trillion) debt relief package in late 2024, it is just a small step in easing financial pressures. With total government debt expected to reach nearly 150 percent of gross domestic product by 2030, local governments will face even greater fiscal strain, which could jeopardize investments in agriculture—such as rural infrastructure and necessary technological innovations.
Although the government has introduced measures, including a 10 billion yuan (US$1.38 billion) subsidy in 2023 to boost farmers’ incomes, these efforts fail to tackle the deeper financial and structural issues. But without comprehensive reforms, China’s agricultural production goals remain at risk.
To this end, working with the private sector, including the country’s leading technology (such as Huawei) and e-commerce platforms companies like Pinduodu and JD.com, which have already demonstrated interest in this area, could help address concerns by deploying scalable, low-risk solutions that reduce upfront costs for farmers and local governments. .
Such collaborations have helped drive much of China’s “AI plus Agriculture” market growth. Valued at 68.5 billion yuan (US$9.55 billion), that figure is projected to exceed 90 billion yuan by 2024, according to Chinese think tank Qianzhan Industry Research Institute, thereby demonstrating that private-sector innovation can sustainably bridge urban-rural divides.
Looking ahead
China’s food security challenges are complex. But AI offers a transformative solution. From increasing agricultural productivity to minimizing waste and enhancing supply chain resilience, AI has the potential to significantly improve China’s ongoing food security efforts.
