## Growing More with Less

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**Canonical URL:** [Growing More with Less](https://www.imf.org/en/publications/fandd/issues/2023/12/case-studies-growing-more-with-less-robert-horn)

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- [Markdown version](/en/publications/fandd/issues/2023/12/case-studies-growing-more-with-less-robert-horn/index.md)
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## Bibliographic details
- Authors: ROBERT HORN
- Published: December 1, 2023

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### AI applications in food and agricultural production
- AI is used to: engineer new varieties of climate resistant rice; provide data on soil; guide drones that precision spray fertilizers and pesticides; and sort, inspect, and grade produce.
- Quotation: “AI-driven smart agriculture provides tremendous potential for boosting food security and to reduce or even end hunger in many regions of the world,” said Channing Arndt, of the Consultative Group on International Agricultural Research.

### Thailand: national strategy and programs
- Thailand 4.0: a 20-year national strategy unveiled in 2014 with priority sectors including food, agriculture, and digital industries.
- Government programs: Smart Farmer and Young Smart Farmer encourage adoption of precision agriculture and connection to new technologies such as AI-controlled drones and intelligent targeted spraying.
- Country context:
  - Population: 70 million people.
  - Rank: the world’s 15th largest food exporter and the only net food exporter in Asia.
  - Projected shipments this year: $44.3 billion.
- Infrastructure and initiatives:
  - THEOS-2: launched in October, the first Earth observation satellite jointly designed by Thai and British engineers to gather data for smart agriculture.
  - One Community, One Drone program: farmers in 500 communities share drone services to manage fields.
  - NIA incubator and accelerator programs source private sector investment for agritech start-ups.
  - DEPA matches tech businesses with markets and funds start-ups.

### Digital agritech startups and partnerships
- Ricult:
  - Founded in 2015.
  - Dual fintech and agritech firm operating in Pakistan, Thailand, and Vietnam.
  - AI-driven app with more than 800,000 downloads in Thailand.
  - Provides tools for crop variety selection, precision methods, and access to finance.
- Corporate partnerships:
  - Mitr Phol Group partnered with IBM for AI-driven data solutions for farmers.
  - Chia Tai uses autonomous drones made by XAG of China.

### Global context and impact on food security
- Recent setbacks in food security:
  - Estimated 735 million people (9.2 percent of the global population) undernourished in 2022, per The State of Food Security and Nutrition in the World.
  - Thailand saw hunger rise for the first time in a decade.
- Drivers of concern:
  - Pandemic, war in Ukraine, and resulting disruptions.
  - Younger farmers migrating to cities, reducing farm labor while food demand grows.
- Potential benefits of AI and digital technologies:
  - Help fewer farmers generate more food.
  - Increase productivity and efficiency across food chains, potentially reducing malnutrition and food scarcity.
- African initiatives and constraints:
  - Some African governments have passed restrictive drone regulations; licensing can be difficult.
  - Countries such as Kenya, Rwanda, Tanzania are investing in building digital ecosystems and literacy so farmers can access online extension services, weather forecasts, market information, and financing.
  - Obstacles: connectivity and digital literacy remain significant challenges.

### Policy observations and recommendations
- Role of government:
  - Governments should act as creators of policies and facilitators of funding for start-ups, innovators, and farmers, rather than micromanaging markets (comment by Ricult cofounder Aukrit Unahalekhaka).
  - Coordinated, non-insulated government action can improve uptake of smart farming.
- Support measures highlighted:
  - Incubators and accelerators to source private investment.
  - Programs to match technology providers with farmer markets.
  - Shared-service models (e.g., community-shared drones) to lower adoption barriers.
  - Investment in digital infrastructure and farmer digital literacy.

### Risks, caveats, and governance
- Data quality risk: “If the data are bad, AI’s results will be bad.”
- Objective alignment risk: AI can be programmed to increase yields while ignoring negative environmental impacts.
- Practical observation: Unahalekhaka has not seen farmers misuse AI so far and believes benefits outweigh risks, motivated by a desire “to make the world a better place.”

*Source: Growing More with Less by Robert Horn, F&D Magazine, December 2023.*

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## Content in this bundle

- **F&D Artificial Intelligence: AI IN PRACTICE- Growing More with Less**
  - [F&D Artificial Intelligence: AI IN PRACTICE- Growing More with Less (Markdown version)](/-/media/files/publications/fandd/article/2023/december/ai-in-practice-case-studies-horn.pdf.md){rel="alternate" type="text/markdown"}
  - [F&D Artificial Intelligence: AI IN PRACTICE- Growing More with Less (PDF)](/-/media/files/publications/fandd/article/2023/december/ai-in-practice-case-studies-horn.pdf){rel="external" type="application/pdf"}

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_Source: https://www.imf.org/en/publications/fandd/issues/2023/12/case-studies-growing-more-with-less-robert-horn_