FICCI and PwC jointly released a study Thursday on the application of Artificial Intelligence in farming practices, ‘Ushering in new growth wave: From Artificial Intelligence to Agricultural Intelligence’ during a webinar, AI & Digital Applications in Agriculture, jointly organised by FICCI and the German Agribusiness Alliance.
The study talks about 10 strategic interventions to catalyse Artificial Intelligence adoption in Indian agriculture.
1.Development of country-specific platform
Development of country-specific platform to address asymmetry in information: It will ensure that multiple data points or knowledge portals are aggregated into a single integrated agriculture platform.
2.Improving digital literacy among farmers
Improving digital literacy among farmers will help bring more imaginative in designing solutions and interfaces that are socially embedded and localised in relation to socio-cultural and agronomic contextualities.
3.Identifying and developing effective channels for dissemination of AI solutions
Identifying and developing effective channels for dissemination of AI solutions among farming communities: Business to farmers channels is suited for disruptive technologies, Digital Agripreneurs– suited for progressive technologies, FPOs – suited for capacity building and Start-up tech companies- Govt collaboration: suited for diffusion tech.
4.Promoting ultimate use of AI data for effective, accessible and affordable solutions
Information sources, such as satellites, drones and weather-related data can be combined with the results of crop-cutting experiments to improve the accuracy of forecasts and many related solutions.
5.Establishment of skill development centres for training on AI tools
Establishment of Skill Development Centres (SDCs) would support the creation of reliable AI-extension experts in the market. A last mile delivery approach.
6.Fostering sustainable linkages among private players
Fostering sustainable linkages among private players and PPP will help to cross pollinate ideas amongst private platforms of varied scale and emerge PPP.
7.Promoting linkages between private players and state agriculture universities
This will help the AI tech to customise the IT tech with agri-tech and hence make more meaningful offerings.
8.Categorisation for effective dissemination of digital technologies
Identification of two broad categories of innovation, i.e. social embeddedness-led innovation and transfer and diffusion-led innovation. This will lead to reduce the adoption lag time and enhance faster technology infusion.
9.Predicting current sowing
Artificial intelligence (AI) can be applied to predict current sowing time and provide advisories on pest and input control. This can help in ensuring increased yield and also reduce effective input costs thereby enhancing farm income.
10.Reducing wastage and losses
AI will immensely help in reducing wastage and losses. It will ensure judicious use of resources, therefore promoting precision farming and enabling sustainable farming systems.