Artificial Intelligence in Indian Agriculture: Adoption Pathways, Data Systems, and Sustainability Outcomes
DOI:
https://doi.org/10.66132/mr010205Keywords:
Precision agriculture, Digital public infrastructure, Climate resilience, Farm decision support, Agricultural innovationAbstract
Artificial Intelligence (AI) is another technology that is starting to be seen as a game changer in Indian agriculture and it could be implemented in the areas of crop management, pests and disease detection, irrigation schedules, market intelligence and livestock systems. The article focuses on a literature review of the academic investigations of the significance of AI applications in Indian agriculture, the data and digital infrastructure about the applications, the sustainability of the AI application use and the policy/governance tools of the AI application uptake. The review points out that the AI has provided hopeful outcomes on productivity enhancement, input-use productivity, pest management, and climate-sensitive decision-making, specifically in the pilot-based advisory regimes. Simultaneously, this is limited by its larger scale, disaggregated data, inequality in digital facilities, lack of interoperability, data regulation problems, and inequalities in access to various farmers. Another finding of this discussion is that AI in the Indian agricultural sector cannot be measured in terms of technical values, and the value of AI will be determined by the level to which it is integrated into the inclusive institutions, trusted and dependable digital infrastructure of the country and responsible governance procedures. The paper finds that AI can be used in transforming agriculture in India to be sustainable significantly, but it must come with the following conditions: working with the help of farmer-centred design, ethical use of data, and implementational models scalable, without references to specific pilot success stories.
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Copyright (c) 2025 Vaishnavi Pulletikurthi, Sai Kumar Periginji, Malireddy Sujohn
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