AI's Next Agritech Frontier Is India's Fragmented Supply Chain
While agritech companies have developed AI tools for crop monitoring, pest detection and yield prediction, India's agricultural value chain remains fragmented across farmers, FPOs, aggregators, traders, processors and retailers using separate record-keeping systems. A 2022 NABARD study estimated post-harvest losses of 6–15% for fruits and 5–12% for vegetables, highlighting operational inefficiencies. AI could forecast availability, plan procurement and assess demand, but requires reliable cross-chain data access. The challenge is less the absence of data than its fragmentation across different stakeholders, systems, languages and applications.
Key points
- Agritech gap lies in supply chain integration, not farm-level monitoring
- Post-harvest losses of 6–15% (fruits) and 5–12% (vegetables) highlight inefficiency
- Data fragmented across farmers, aggregators, mandis, retailers and processors
- AI applications depend on cross-chain data access and unified recordkeeping
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