(untitled) (Tejganga Darpan, 2026)
Artificial Intelligence (AI) is increasingly shaping agribusiness transformation in Nepal by improving productivity, sustainability, and market integration within a largely smallholder-based agricultural economy. This article examines the current status, applications, opportunities, and constraints of AI adoption in Nepal’s agribusiness sector using a comprehensive secondary desk review of academic literature, policy documents, and development reports. Key AI applications include precision farming, satellite-based crop classification, predictive analytics, and digital advisory services across crop, livestock, and supply chain management. Initiatives such as GeoKrishi, Connect Kisan AI, and the Omdena-UNWFP collaboration illustrate AI’s potential to enhance resource efficiency and climate resilience. However, adoption remains limited due to infrastructure gaps, high costs for smallholders, data scarcity and localization challenges, low digital literacy, and evolving policy and regulatory frameworks. Drawing on insights from other emerging markets, the study adapts the extended Technology Acceptance Model-Technology-Organization-Environment (TAM-TOE) framework to contextualize AI adoption in Nepal. The article concludes that inclusive and scalable AI-driven agribusiness transformation will require coordinated stakeholder engagement, targeted investments in digital infrastructure, skills development, and robust data governance mechanisms.