OECD: Artificial Intelligence for Resilient and Inclusive Agri-Food Systems
The OECD analyzes how artificial intelligence can strengthen global food systems under pressure from climate, fragile supply chains, and labor shortages. The text highlights three barriers — siloed data, poor accessibility for smallholder farmers, and barriers to scaling. It recommends stronger international cooperation through the OECD and GPAI.
This article was generated using artificial intelligence from primary sources.
The OECD published an analysis on June 5, 2026, through its OECD.AI Wonk platform, authored by Marten van den Berg and Sara Rendtorff-Smith, on how artificial intelligence can strengthen global agri-food systems (agricultural-food systems). The text starts from the fact that these systems are under growing pressure from climate change, fragile supply chains, and labor shortages.
Why are food systems under pressure?
The global production and distribution of food face a series of simultaneous challenges. Climate change alters growing conditions and increases the frequency of droughts, while supply chains are increasingly vulnerable to disruptions. Added to this is the labor shortage in agriculture, which further burdens production.
In such a context, the OECD sees artificial intelligence as a tool that can increase the resilience and inclusiveness of systems — that is, make them more capable of withstanding shocks and more accessible to all stakeholders, not just large players.
What three key barriers does the OECD identify?
The analysis highlights three barriers. The first is siloed data: agricultural data is divided among ministries, chain actors, and countries, so it cannot flow freely to where it would be most useful. This fragmentation hampers the development of effective AI solutions.
The second barrier is accessibility. Most AI tools do not reach smallholder farmers, even though they grow roughly a third of the world’s food. The reason is a lack of digital infrastructure among these producers. The third barrier concerns scaling: the spread of successful pilot projects is hampered by cyber threats and an infrastructure gap.
What is the real potential of AI in agriculture?
To illustrate the possibilities, the OECD cites concrete examples. Precision spraying, in which AI directs the application of agents exactly where needed, can reduce pesticide use by 30%. This brings both ecological and cost savings.
Another example concerns resilience to climate shocks: AI-identified drought-resistant crops can raise yields by 25% in dry seasons. Such results show that the technology already offers tangible benefits — provided it can be scaled beyond the pilot phase.
What does the OECD recommend?
The main recommendation of the analysis is stronger international cooperation. The OECD calls for coordination through its own mechanisms and through GPAI (Global Partnership on AI) to build interoperable data ecosystems — systems in which data can flow securely and meaningfully among stakeholders.
The other emphasis is on farmer-centered solutions, especially for smallholder producers who have so far been beyond the reach of AI tools. With this, the OECD links technological potential with the question of fairness: the benefit of artificial intelligence in food systems should reach those who grow a significant portion of the world’s food, rather than remaining reserved for the most digitally equipped players.
Frequently Asked Questions
- What are agri-food systems?
- Agri-food systems (agricultural-food systems) encompass the entire chain from producing food in the fields, through processing and supply, to food reaching the consumer. In its analysis, the OECD examines how artificial intelligence can make these systems more resilient to shocks and more inclusive for all stakeholders, including smallholder farmers.
- What three key barriers does the OECD identify?
- The OECD highlights three barriers. The first is siloed agricultural data divided among ministries, chain actors, and countries. The second is the poor accessibility of AI tools to smallholder farmers who lack digital infrastructure. The third is cyber threats and an infrastructure gap that hamper the scaling of successful pilot projects.
- What concrete gains can AI bring in agriculture?
- According to the examples cited by the OECD, precision spraying can reduce pesticide use by 30 percent, while AI-identified drought-resistant crops can raise yields by 25 percent in dry seasons. These examples illustrate the technology's potential, but the OECD stresses that stronger international cooperation is needed to spread them.
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