Google Launches AI Tools for Indian Farms and Cultural Diversity Amid Tech Adoption Hurdles

Google launched open-source artificial intelligence (AI) initiatives on July 11, to accommodate India’s agriculture sector, linguistic and cultural diversity in AI models. The company launched the Agricultural Monitoring and Event Detection (AMED) Application Programming Interface (API), which provides information on crops and field activity across India to help developers build targeted solutions for agricultural productivity and resilience, reported ANI.

Researchers at Google DeepMind collaborated with IIT-Kharagpur through the company’s Amplify Initiative to build datasets on India’s linguistic and cultural diversity for integration into large language models (LLMs).

"We've been inspired by the solutions India's innovators have unlocked with these capabilities, demonstrating AI to be a powerful catalyst for multiplier impact and unprecedented effectiveness,” said Dr Manish Gupta, senior director for India and Asia Pacific (Apac) at Google DeepMind, during a roundtable in Bengaluru, cited ANI.

Google DeepMind and the Partnerships Innovation team have developed AMED API to build upon the company’s Agricultural Landscape Understanding (ALU) API and now leveraging machine learning, crop labels, and satellite imagery to identify crop types, field sizes, and sowing and harvesting dates. The API also provides three years of historical data to track agricultural activity in the field level.

While technology is being deployed for improving of agricultural produce, yet widespread technological adoption among India’s low-income farmers remains a challenge.

Transformation at a Cost

According to a February 2025 Future Farming in India report published by the World Economic Forum, while the AI-driven transformation of agriculture may have begun, deploying technology at scale is not easy.

Experts believe that fewer than 20% of Indian farmers use digital technologies, which are a superset of AI-enabled solutions. Otherreasons for this low rate of adoption include the low income of Indian farmers (around $1,500 annually) which restricts both their ability and willingness to pay for AI solutions.

Without appropriate financing support, technology interventions are perceived to be an added burden, given the already increasing cost of cultivation, stated the WEF report. 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).

Small and fragmented landholdings significantly increase the cost of delivering AI solutions in rural settings. This results in solution providers to focus primarily on larger farmers or businesses. On the supply side, the development and use of AI solutions involves real-time data and investment in investment in infrastructure and resources, which further drives up the cost of AI development.

With limited mechanisms for validating technology before it is deployed, many farmers remain wary of adopting them.