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Unlocking AI's Potential in Agriculture: The Critical Role of Data

Author

Listed:
  • K. B. Vedamurthy
  • Manojkumar Patil
  • Vaishnavi
  • Priyanka V
  • Suman L
  • Ajayakumar
  • Sagar

Abstract

India generates substantial volumes of public agricultural data, yet artificial intelligence (AI) adoption in farming remains limited and largely confined to pilot initiatives. This paper examines this gap by assessing India's agricultural data infrastructure against the requirements of AI systems deployed at scale. Drawing on a systematic review of major national datasets and digital initiatives including Soil Health Cards, crop insurance, AgriStack, and selected state platforms we identify persistent structural constraints, including temporal misalignment between data collection and agricultural decision cycles, spatial fragmentation arising from the absence of common geocodes linking soil, weather, and yield information, limited machine readability due to reliance on static data formats, and unclear governance frameworks that restrict data access and reuse. These deficiencies impede cross-dataset integration and automated decision support, with disproportionate consequences for smallholders, who constitute 86~\% of India's farmers and lack the capacity to compensate for weak data infrastructure. Drawing on implementation evidence from India and comparative international experiences, the paper identifies recurring features associated with scalable digital agriculture systems, including incentives linked to data provision, service bundling through local institutions, and sensor-enabled risk management.

Suggested Citation

  • K. B. Vedamurthy & Manojkumar Patil & Vaishnavi & Priyanka V & Suman L & Ajayakumar & Sagar, 2026. "Unlocking AI's Potential in Agriculture: The Critical Role of Data," Papers 2603.23289, arXiv.org, revised Mar 2026.
    • Handle: RePEc:arx:papers:2603.23289
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    References listed on IDEAS

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    1. Marie-Agnes Jouanjean & Francesca Casalini & Leanne Wiseman & Emily Gray, 2020. "Issues around data governance in the digital transformation of agriculture: The farmers’ perspective," OECD Food, Agriculture and Fisheries Papers 146, OECD Publishing.
    2. World Bank, "undated". "Enabling the Business of Agriculture 2019," World Bank Publications - Reports 31804, The World Bank Group.
    3. Saifuddin, Md. & Devy, M. Rama & Rao, M. S. & Suseela, K., 2023. "Effectiveness of Rythu Bharosa Kendras (RBKs) Services as Perceived by Farmers in the East Godavari District of Andhra Pradesh, India," Asian Journal of Agricultural Extension, Economics & Sociology, Asian Journal of Agricultural Extension, Economics & Sociology, vol. 41(4), pages 1-7.
    4. Ania Cravero & Sebastián Pardo & Patricio Galeas & Julio López Fenner & Mónica Caniupán, 2022. "Data Type and Data Sources for Agricultural Big Data and Machine Learning," Sustainability, MDPI, vol. 14(23), pages 1-37, December.
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