China AI in Agriculture Market By Technology (Machine Learning, Predictive Analytics and Computer Vision), By Offering (Hardware, Software and AI-As-A-Service), By Application (Precision Farming, Livestock Monitoring, Agriculture Robots, Drone and Others), By Region, Competition, Forecast and Opportunities, 2021-2031F

Forecast Period	2027-2031
Market Size (2025)	USD 153.12 Million
CAGR (2026-2031)	7.91%
Fastest Growing Segment	Machine Learning
Largest Market	East
Market Size (2031)	USD 241.77 Million

Market Overview

The China AI in Agriculture Market will grow from USD 153.12 Million in 2025 to USD 241.77 Million by 2031 at a 7.91% CAGR. The China AI in Agriculture market is defined by the deployment of advanced computational systems, including predictive analytics, computer vision, and autonomous robotics, to optimize crop cultivation, livestock monitoring, and resource management. The primary drivers supporting this sector’s expansion are the critical national imperative for food security and the urgent need to mitigate labor shortages caused by an aging rural population and urbanization. These drivers are accelerating the transition from traditional farming to intelligent mechanization. According to the Ministry of Agriculture and Rural Affairs, in 2024, the comprehensive mechanization rate of crop cultivation and harvest nationwide reached 74%, establishing a substantial hardware foundation necessary for the integration of advanced artificial intelligence software.

Despite the favorable regulatory environment, the market faces a significant challenge regarding the high implementation costs and the fragmentation of agricultural data. The substantial capital expenditure required for intelligent machinery and sensor networks creates a barrier to entry for smallholder farmers who dominate the agricultural landscape but lack the financial resilience to invest in premium digital solutions. This economic disparity, coupled with a lack of standardized data infrastructure in remote provinces, complicates the scalable adoption of AI technologies and limits the market’s penetration into less developed regions.

Key Market Drivers

Robust Government Policy Support and Strategic Smart Agriculture Action Plans serve as the foundational catalyst for the China AI in Agriculture market. The central government has prioritized the digital transformation of farming to ensure national food security, implementing substantial financial subsidies that lower the entry barrier for advanced machinery. According to the State Council Information Office, May 2024, in the 'briefing on China's fiscal revenue and expenditure', the central government allocated 24.6 billion yuan to support subsidies for the purchase and application of agricultural machinery. This fiscal injection directly incentivizes the adoption of AI-embedded systems, allowing cooperatives and large-scale farms to integrate predictive analytics and automated control systems into their operations, thereby accelerating the modernization of the sector in line with the national digitization strategy.

The Proliferation of Agricultural Drones and Autonomous Robotics Technology is the second critical driver, fundamentally altering traditional labor-intensive practices. As rural workforces shrink, autonomous aerial and ground vehicles are becoming essential for tasks ranging from precision spraying to crop monitoring, effectively compensating for human labor deficits. According to China Daily, August 2025, in the 'White Paper on the Agricultural Drone Industry (2024/2025)', agricultural drones in China completed work covering more than 173 million hectares in 2024. This massive operational scale demonstrates how autonomous hardware enhances precision and efficiency across vast planting areas. Consequently, this technological integration is vital for maintaining productivity; according to the Ministry of Agriculture and Rural Affairs, November 2024, in a statement regarding the 'smart agriculture action plan', China's grain output was set to exceed a record 700 million tonnes in 2024, underscoring the role of intelligent mechanization in stabilizing national food supplies.

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Key Market Challenges

The high implementation costs and the fragmentation of agricultural data constitute a formidable barrier to the growth of the China AI in Agriculture market. The substantial capital expenditure required for intelligent machinery and sensor networks prevents smallholder farmers, who dominate the landscape, from adopting these advanced technologies. Without the financial resilience to invest in premium digital solutions, a large segment of the agricultural sector remains excluded from the benefits of AI, such as predictive analytics and autonomous robotics. This economic divide limits the market's reach primarily to well-funded, large-scale agribusinesses, thereby stifling broader industry expansion and slowing the transition to intelligent mechanization.

Furthermore, the lack of standardized data infrastructure in remote provinces complicates the scalable application of AI, as these systems rely heavily on robust data streams and interconnected hardware. The financial strain on the sector is reflected in recent equipment adoption trends, which signals a slowdown in the necessary hardware investment. According to the China Association of Agricultural Machinery Manufacturers, in 2024, the overall sales volume of agricultural machinery nationwide declined by 13% compared to the previous year. This contraction in hardware acquisition indicates a significant reluctance or inability among farmers to commit to capital-intensive investments, directly hindering the deployment of the physical platform necessary for AI integration.

Key Market Trends

The Integration of Generative AI and Large Agricultural Models represents a cognitive leap in the market, moving beyond simple perception tasks to complex decision-making and advisory roles. Unlike traditional predictive analytics that rely heavily on structured data, these large language models (LLMs) synthesize massive amounts of unstructured information—such as academic literature, real-time weather patterns, and visual pest data—to generate actionable agronomic prescriptions. This trend empowers software to function as a virtual expert, effectively democratizing access to high-level agricultural knowledge for operators lacking specialized training. According to Xinhua, October 2025, in the article 'Chinese university unveils new AI model for agriculture', China Agricultural University launched the Shennong Large Model 3.0, which utilizes training on over 10 million agricultural knowledge graphs to deliver precise breeding and planting guidance, illustrating the rapid commercialization of domain-specific AI brains.

The Emergence of Fully Autonomous Unmanned Farms is shifting the industry focus from isolated smart devices to holistic, interconnected production ecosystems. This trend involves the synchronization of ground-based robotics, aerial drones, and soil sensors into a unified operational grid, managed by a central digital twin rather than human pilots. The scalability of these unmanned systems is heavily dependent on high-precision positioning infrastructure, which allows disparate machinery to coordinate complex tasks like sowing and harvesting without collision or overlap, effectively creating a factory-floor environment outdoors. According to Global Times, July 2025, in the article 'China's Gen Z farmers embrace smart agriculture', the installed base of intelligent equipment supporting this transition has expanded significantly, with more than 2.2 million agricultural machines nationwide equipped with the BeiDou navigation system by 2024.

Segmental Insights

The Machine Learning segment represents the fastest-growing category within the China AI in Agriculture Market, driven by the increasing necessity for data-driven decision-making in crop management. Chinese agricultural operators actively deploy these algorithms to analyze inputs from remote sensors, enabling accurate yield forecasting and early pest detection. This trajectory aligns with strategic objectives from the Ministry of Agriculture and Rural Affairs to modernize farming through digital technologies. Furthermore, the capability of machine learning to automate complex analysis and optimize resource allocation significantly accelerates its adoption amidst the ongoing transformation of the regional agricultural landscape.

Regional Insights

East represents the leading territory within the China AI in Agriculture Market, driven by a high concentration of technology enterprises in Shanghai, Jiangsu, and Zhejiang. This region benefits from established digital infrastructure and substantial investment in modernization projects. The Ministry of Agriculture and Rural Affairs frequently selects these provinces for pilot smart farming initiatives, accelerating the deployment of automated machinery and intelligent monitoring systems. As a result, East China maintains a commanding position through the consistent integration of artificial intelligence into crop management and operational decision-making processes.

Recent Developments

• In October 2025, Syngenta Group announced a strategic expansion of its digital agriculture operations in China, pledging to deepen the integration of artificial intelligence within its Modern Agriculture Platform (MAP). A senior executive revealed that the company would leverage advanced AI technologies to analyze soil health and crop performance data, thereby optimizing input usage and increasing grain output in key production regions. The announcement detailed plans to upgrade the company's service centers with intelligent systems that offer full-cycle solutions, from seed selection to crop protection. This move reinforced the company's commitment to modernizing China's agriculture through data-driven innovation and sustainable farming practices.
• In March 2025, Tencent and Alibaba introduced new artificial intelligence tools specifically tailored for the agricultural sector in rural China. These tools, powered by the companies' respective large language models, were designed to provide farmers with real-time agronomic advice, pest identification, and crop management insights through accessible mobile interfaces. The deployment of these AI solutions aimed to bridge the digital divide by offering sophisticated data analytics and generative AI capabilities to smallholder farmers, enabling them to make informed decisions regarding planting and harvesting. This development marked a significant collaboration between China's leading technology firms and the agricultural industry to digitize rural production.
• In December 2024, Pinduoduo concluded its fourth Smart Agriculture Competition in Shanghai, an event that brought together data scientists and agricultural researchers to develop AI-driven planting models. The competition focused on utilizing artificial intelligence and algorithms to control environmental variables in greenhouses, such as temperature and humidity, to maximize crop yields and quality. The participating teams demonstrated how digital technologies could be applied to traditional farming practices, achieving significant breakthroughs in production efficiency. This initiative highlighted the e-commerce platform's continued investment in fostering breakthrough research and facilitating the adoption of smart agriculture technologies across China.
• In November 2024, XAG hosted its annual conference in Guangzhou, where the company launched its latest agricultural innovations, including the P150 agricultural drone. This new unmanned aerial vehicle was introduced with advanced artificial intelligence capabilities designed to enhance precision in autonomous farming operations such as spraying, spreading, and field mapping. The company highlighted the drone's improved payload capacity and intelligent flight control systems, which utilize AI to optimize flight paths and obstacle avoidance in complex rural environments. This launch underscored the company's focus on integrating smart hardware with digital farming infrastructure to improve operational efficiency for Chinese farmers.

Key Market Players

• IBM China Company Limited
• Microsoft (China) Co., Ltd.
• Agriplus Ltd.
• Beijing DBN Technology Group Co., Ltd
• Suzhou Eavision Robotic Technologies Co., Ltd.
• Shenzhen Han's Robot Co., Ltd.
• Yunqi Technology
• XAG Co., Ltd.
• Baidu, Inc.
• Shenzhen Huayun Information System & Technology Co., Ltd.

By Technology	By Offering	By Application	By Region
Machine Learning Predictive Analytics Computer Vision	Hardware Software AI-As-A-Service	Precision Farming Livestock Monitoring Agriculture Robots Drone Others	North North-East East North-West South-Central South-West

Report Scope:

In this report, the China AI in Agriculture Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

• China AI in Agriculture Market, By Technology:

• Machine Learning
• Predictive Analytics
• Computer Vision

• China AI in Agriculture Market, By Offering:

• Hardware
• Software
• AI-As-A-Service

• China AI in Agriculture Market, By Application:

• Precision Farming
• Livestock Monitoring
• Agriculture Robots
• Drone
• Others

• China AI in Agriculture Market, By Region:

• North
• North-East
• East
• North-West
• South-Central
• South-West