How AI’s Role in Agriculture is Transforming Supply Chains

Investment in AI within the farming sector is poised to surge over the next three years. In fact, forecasts suggest it will nearly triple, growing from US$1.7bn to US$4.7bn by 2028.

This rapid growth reflects agriculture's readiness to embrace AI to address its pressing challenges, especially in supply chains and sustainable farming.

The focus is clear: AI simplifies complex processes, enabling farmers to improve efficiency, reduce costs and boost yields.

With climate change, population growth and consumer demand for sustainability putting immense pressure on food supply chains, AI is emerging as a key tool to help farmers balance environmental goals with economic viability.

Jeff Rowe, CEO of Syngenta Group, explains: "Predictive performance analytics are revolutionising farm management by harnessing historical data through artificial intelligence and machine learning."

Regenerative farming: A sustainability game-changer

Agriculture is responsible for about a quarter of global greenhouse gas emissions, positioning it as a major contributor to climate change.

However, it also has the potential to play a pivotal role in sustainability, particularly through regenerative farming practices.

Regenerative agriculture focuses on enhancing soil health, biodiversity and ecosystem resilience. Practices such as reduced tillage, cover cropping and crop rotation improve soil fertility and carbon sequestration.

"At its core, regenerative agriculture is about working with nature, not against it," adds Jeff, who has implemented these techniques on his 3,000-acre Illinois farm.

By adopting no-till farming and precision input application, Jeff has observed measurable benefits: "We’ve seen higher levels of organic matter and active carbon, as well as increases in water retention and nutrient availability."

Studies suggest that expanding regenerative practices to 40% of global farmland could significantly strengthen food systems while curbing environmental degradation.

Yet, adopting these methods involves substantial investment in new knowledge, equipment and time—resources not all farmers can easily access.

AI-powered solutions for agricultural productivity

AI and digital tools are helping bridge the gap between traditional farming and regenerative practices.

Technologies like satellite imagery, drone monitoring and soil mapping provide farmers with real-time insights into field conditions. These tools enable precise resource application—water, fertilisers and pesticides—thereby reducing waste and mitigating farming’s environmental impact.

Jeff highlights the importance of data-driven decision-making: "By analysing historical and real-time data, farmers can anticipate issues like pest outbreaks or soil nutrient deficiencies, making informed decisions that boost yields while minimising ecological harm."

The financial benefits of precision agriculture are compelling. Research suggests that farmers using these methods could see profit increases of up to 120%. In low- and middle-income countries, digital technologies have the potential to add more than US$450bn annually to agricultural GDP, improving both productivity and equity.

AI's role extends to optimising supply chains, from predicting crop yields to tracking produce through every stage of delivery. This transparency ensures better planning, reduces food waste and strengthens the resilience of food systems in the face of external shocks like climate change.

Policy and industry collaboration is key 

Despite AI’s promise, adoption remains uneven, with many farmers struggling to overcome financial and technical barriers. Policymakers and industry leaders must step up to create an enabling environment.

Financial incentives, such as grants or subsidies for adopting sustainable technologies, could ease the transition. Carbon markets, which reward farmers for carbon sequestration, are another avenue for economic support.

Jeff emphasises the importance of collaboration: "Policymakers, businesses and governmental bodies must work together to address farmers' financial and technological requirements."

Expanding education and training can also empower farmers to embrace AI and regenerative methods effectively.

The private sector is already demonstrating the power of partnerships.

Syngenta’s collaboration with McDonald’s and Lopez Foods has improved sustainability in beef production, showcasing how supply chain cooperation can yield tangible benefits.

Katie Kurz, Syngenta’s Global Head of Executive Communications, notes: "By working together, we can uncover new opportunities, build resilience and grow."

While AI-driven farming may reduce demand for certain products like traditional pesticides, it aligns with a broader vision for the future.

Jeff concludes: "Our guiding principle is to create more value for our customers by developing solutions that help farmers to sustainably produce healthy food for society."

Through innovation and collaboration, AI is not only transforming agriculture but also paving the way for sustainable supply chains and a resilient future.

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