Harnessing Artificial Intelligence for Agricultural Advisory Services: A Critical Review of Farmer Led Experiences with the ‘Ama Krushi’ Chatbot in Odisha
Soubhagya Kumar Sahoo
*
Department of Agricultural Extension and Communication, Faculty of Agricultural Sciences, Siksha ‘O’ Anusandhan Deemed to be University, Bhubaneswar, Odisha, India.
Anshuman Jena
Department of Agricultural Extension and Communication, Faculty of Agricultural Sciences, Siksha ‘O’ Anusandhan Deemed to be University, Bhubaneswar, Odisha, India.
*Author to whom correspondence should be addressed.
Abstract
Artificial Intelligence (AI) is reshaping agricultural extension by enabling real-time, personalized advisory services. This review critically evaluates the 'Ama Krushi' chatbot, an AI-powered extension platform launched in Odisha under the World Bank-supported SMART Agriculture Project. Leveraging Natural Language Processing, the chatbot delivers localized advisories in Odia and Sambalpuri, reaching over 1.5 million farmers since 2019. AI in agriculture has demonstrated potential to improve decision-making through real-time analytics and personalized recommendations. Chatbot platforms enhance access to information in underserved regions. Farmer-led assessments involving 1,200 users indicated that 74% found the service accessible, 68% deemed the content relevant, and 52% reported improved input use and crop planning. Comparative analysis with platforms like mKisan and e-Choupal shows that localized AI tools enhance engagement and relevance. Despite Odisha’s 85% rural mobile penetration (TRAI, 2024), barriers persist—especially among women and tribal populations—due to digital divides and limited offline support. The review advocates a systems-level strategy for AI integration, emphasizing co-design, multilingual access, and hybrid (AI + human) models. The Ama Krushi experience offers valuable insights for developing scalable, inclusive, and ethically grounded AI-driven extension services tailored to smallholder needs in the Global South.
Keywords: Machine learning, chatbot, artificial intelligence, farmer-led assessment, ICT, digital literacy, decision-making