While the AI-driven transformation of agriculture may have begun, deploying technology at scale is not easy, the report finds. Its use is still limited in agriculture: according to experts, fewer than 20% of Indian farmers use digital technologies, which are a superset of AI-enabled solutions. There are several reasons for this low rate of adoption. For instance, the low income of Indian farmers (around $1,500 annually) restricts both their ability and willingness to pay for AI solutions.
Without financing support, technology interventions are perceived to be an added burden, given the already increasing cost of cultivation. Additionally, close to 85% of India’s 150 million farmers are smallholders, and the Indian farmer’s average landholding is just 1.08 hectares (about 2.67 acres). “With such small landholdings, which are often fragmented, the cost of delivering AI solutions in rural settings increases tremendously,” says the report.
On the supply side, the development and use of AI solutions rely on the collection of large volumes of data, often in real time, which requires investment in infrastructure and resources, and this drives up the cost of AI development. “This indirectly increases the cost of services, further affecting their affordability.”
Additionally, there are very limited institutional mechanisms for validating technology before it is deployed, increasing the perceived risk of adoption.