China’s AI-driven agriculture offers lessons for emerging markets, Syngenta executive says

AI News


(Yicai), Jan. 21 — China’s use of artificial intelligence in agriculture is an important case to watch and could provide valuable lessons for other emerging markets, a senior executive from the world’s largest agricultural technology company Syngenta Group told Yicai at the World Economic Forum, which opened yesterday in Davos, Switzerland.

AI in agriculture in China is not about creating the most complex models, said Feroz Sheikh, chief information and digital officer at Basel-based Syngenta. Rather, it is integrated into practical tasks such as identifying crop pests and diseases, determining the best time to spray pesticides, and issuing weather warnings, all displayed in the local language.

“If technology cannot directly help farmers make better day-to-day decisions, it will be difficult to use it at scale,” Sheikh said.

In recent years, AI has been adopted as a core driver of productivity across many industries, including finance, manufacturing, energy, and healthcare. However, adoption in agriculture has been slow.

Sheikh said the slow pace of adoption reflects the need for caution in risk-sensitive areas rather than any fundamental limitations of the technology itself. Agriculture is very complex and highly sensitive to risk. Misapplication of technology can have a direct impact on farmers’ livelihoods.

Unlike the financial and internet sectors, agriculture has no shortage of proof-of-concept projects, Sheikh said. The real challenge is replicable and sustainable large-scale applications. In many emerging countries with large numbers of smallholder farmers, teaching them how to use AI is often more important than the capabilities of the AI ​​model itself.

In this context, the Chinese example is important not only because of its market size, but also because it shows practical paths for agricultural AI, such as the proliferation of digital tools, improved infrastructure, and coordination across industrial chains, which will help AI move from experimentation to everyday decision-making, Sheikh said.

Editor: Du Chicon, Kim Taylor



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