Future Farming in India A Playbook for Scaling Artificial Intelligence in Agriculture 2025

The leader of this stream is the start-up, technology and innovator community. The AI start-ups go through the typical cycles of funding and development, but with a difference under the IMPACT model. They perform activities to achieve convergence and to create a win–win situation for all. For instance, they cooperate with the potential consumers – governments, business and industry – to develop ideas that can solve real-world problems in a unique way. They also collaborate to develop open specifications, open standards and implementation models. Collectively, they strive to create new markets in which everyone will have a share. They also receive mentoring on domain issues from academics, and benefit from the results of their research, which can be applied to society. Co-innovate for AI products with academia and research India, with more than 97 Indian Council of Agriculture Research institutes32 and 53 agricultural universities across the country, offers the largest national agricultural research system in the world. Such research institutions have great potential to be catalysts for collaboration with start-ups and industry in the development of open-source AI models for the agricultural sector. AgHub Telangana,33 the UK’s Agri-Tech Catalyst34 and the Netherlands’ Wageningen University are examples, supporting partnerships between start-ups and researchers. Sandboxes for certification and validation AI sandboxes establish a transparent and efficient platform for validation and certification of AI solutions from three perspectives: governance; domain applicability of agriculture; and technology. Telangana’s agritech sandbox framework is an excellent example for adoption. In addition, the Reserve Bank of India (RBI) and the NHA regulatory sandboxes for fintech and the healthcare sector respectively are good examples for validating AI solutions in a controlled setting. Pilots and showcases Establishing a network of demonstration farms in diverse agricultural zones is essential for AI solutions in real-world environments, allowing developers to refine technologies based on practical feedback and build trust for adoption. The World Economic Forum’s Saagu Baagu35 project in Telangana showcases tangible benefits of AI tools at scale. In addition, Mahindra Agri has established a network of more than 6,000 demonstration farms to provide insights into the performance of AI solutions in different environments. Collaboration platforms Collaboration platforms can be hotbeds of innovation by bringing together stakeholders to promote creativity and problem-solving. Y Combinator,36 the Israel Innovation Authority,37 T-Hub (Telangana)38 and the K-Tech (Karnataka)39 hub have successfully nurtured start-ups by providing seed funding and mentorship. AI infrastructure The IndiaAI Mission is enabling a scalable AI computing ecosystem with more than 10,000 graphic processing units (GPUs) through public– private partnerships to meet the demands of India’s growing AI start-ups and research community and AI marketplace. It will offer AI as a service and pre-trained models, serving as a central hub for essential AI resources. Once all these elements are in place, they will cumulatively bridge the gap between innovation and applications, which will accelerate the development and deployment of AI-driven solutions for agriculture.Create Pillar 2 Start-up and innovation communityCo-innovation support Sandboxes and validation platforms AI infrastructure Collaboration platforms Create Pilot supportCreate pillar of the IMPACT AI framework FIGURE 14 This stream is where innovation happens. Future Farming in India 33