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Home » Syngenta Exec: China’s AI Farming Sets Example for Emerging Markets

Syngenta Exec: China’s AI Farming Sets Example for Emerging Markets

Fahad Khan by Fahad Khan
January 21, 2026
in Business
Reading Time: 1 min read
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Syngenta Exec: China’s AI Farming Sets Example for Emerging Markets
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China’s adoption of artificial intelligence in agriculture serves as a noteworthy example that could offer valuable insights for other emerging markets, according to a senior executive from the world’s leading agricultural technology firm, speaking at the recent World Economic Forum in Davos, Switzerland.

In China, AI is not focused on developing the most sophisticated models. Instead, it is embedded in practical tasks such as detecting pests and plant diseases, determining optimal times for pesticide application, and providing weather alerts—all communicated in the local language, explained Feroz Sheikh, chief information and digital officer based in Basel.

“If a technology doesn’t help farmers make better everyday decisions directly, it will struggle to achieve widespread use,” Sheikh emphasized.

While many sectors—finance, manufacturing, energy, healthcare—have rapidly integrated AI to boost productivity, adoption in agriculture has been more gradual.

Sheikh attributes this slower adoption rate to the need for caution in a highly risk-sensitive industry, rather than any inherent technological limitations. Agriculture is complex and vulnerable, with errors in applying new technology potentially impacting farmers’ livelihoods directly.

Unlike in finance or tech, where proof-of-concept projects are abundant, agriculture faces the real challenge of creating large-scale, replicable, and sustainable solutions. For many developing countries dominated by smallholder farmers, training farmers to use AI often proves more critical than the raw capabilities of the AI itself.

In this context, China’s experience is particularly relevant—not only because of its large market but also because it illustrates a practical approach for deploying agricultural AI. This includes expanding digital tools, enhancing infrastructure, and coordinating across the supply chain, all of which help transition AI from experimental projects to tools integrated into daily farming decisions, Sheikh noted.

Note: Dou Shicong, Kim Taylor

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Fahad Khan

Fahad Khan

A Deal hunter for Digital Phablet with a 8+ years of Digital Marketing experience.

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