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BEIJING, July 4 (China Economic Net) - A robot working in a kiwifruit orchard may be one of the clearest images of how artificial intelligence is reaching China’s farms.

At the 2026 Global Digital Economy Conference (GDEC) held in Beijing from July 2 to 5, a four-armed machine designed to pollinate flowers and harvest kiwifruit was presented as a response to a familiar pressure in fruit production. Both tasks require large amounts of labour and must be completed within limited time windows. According to Datian Farming, the robot can identify flowers and fruit, navigate through orchards and coordinate its arms to carry out pollination and harvesting.

The technology is still highly specialised. Yet it reflects a broader change in the way AI is being introduced into agriculture. The focus is increasingly on parts of farming where labour is difficult to secure, decisions depend heavily on experience, or information arrives too late to be useful.

China's State Council has issued a plan in June to accelerate agricultural and rural modernization during the 15th Five-Year Plan (2026-2030) period. According to the plan, the country will seek to scale up more pioneering industries, such as intelligent design breeding, new energy agricultural machinery, low altitude agricultural economy, agricultural bio manufacturing, and new foods over the coming years.

Greenhouses provide another example. Managing temperature, humidity, irrigation and fertiliser requires constant adjustment, particularly in large connected facilities. Beijing Digital Agriculture and Rural Development Promotion Center said its AI-based greenhouse system links sensors, crop-growth models and control equipment, allowing environmental and crop data to feed into water-and-fertiliser management.

The aim is not to remove farmers from the process. It is to make technical knowledge easier to apply across more production sites. A separate project from Beijing Academy of Agriculture and Forestry Sciences combines Internet of Things sensing, AI analysis and remote expert guidance, allowing agricultural specialists to review real-time environmental and crop-growth data and provide support throughout a growing cycle.

These local innovations align closely with national targets. Under the Ministry of Agriculture's Action Plan, China aims to fundamentally establish its National Agricultural Base Model and Algorithm Open Platform and base model libraries by the end of 2026, accelerating the deployment of large AI models in greenhouse controls and crop growth analysis.

The same logic is extending beyond individual farms. Gago Group said its agricultural model combines satellite remote sensing, weather information and Internet of Things data to analyze conditions through a space-based and ground-based data system. The company said the model can process different forms of spatiotemporal data and produce structured analysis results.

For agricultural companies, AI is also beginning to affect decisions after products leave the farm. A Beijing-based representative of a major multinational agribusiness told China Economic Net that the company has developed an AI system for its layer poultry business that uses information on prices, demand and competing products to support inventory allocation and regional distribution.

The deployment of these individual systems reflects a broader domestic push toward structural efficiency. According to data from the Ministry of Agriculture and Rural Affairs, China’s agricultural science and technology contribution rate has risen to over 64%. As these commercial technologies shift from exhibition displays to regional implementation, they provide pragmatic solutions to stubborn structural pressures.