It is an outcome of WEF’s AI for Agriculture Innovation (AI4AI) initiative, which aims to scale agritech (agricultural technology) services through public-private partnerships.
- It elaborates on the role of agritech in shaping the agriculture ecosystem across four broad categories (see table).
Category | Work Area | Use Cases |
Intelligent crop planning | Creating a detailed, market-oriented and sustainable crop plan. | Gene Editing and use of AI, soil testing-based advice. |
Smart Farming | Use of technologies to improve efficiency in farm operations. | AI and Augmented Reality (AR) for crop planning, hyperlocal weather predictions, yield prediction and distributed ledger-based index insurance. |
Farmgate-to-fork | Connecting farmers to market and addressing underlying issues like crop loss between farm and market. | Traceability, Internet of Things (IoT) enabled warehousing, smart logistics. |
Data as an enabler | Ease of access to high quality, usable data. | Use of Digital Public Infrastructure (DPI) for farmers’ welfare. |
Challenges in agritech adoption:
- High up-front acquisition costs and lack of uniform standards.
- Farm data sharing and ownership issues.
- Unclear return on investment.
Way forward:
- Gender-inclusive digital architecture.
- Public–private partnership for scaling agritech.
- Educate and generate interest in farmers.
India’s Initiative for Agritech adoption
|