Digitalization in Agriculture Marketing: The Function of Big Data and AI in Government Programs

Abstract

The agricultural industry has seen a transformation thanks to the digitalization of agricultural marketing, which has improved farmer accessibility, efficiency, and transparency. Government initiatives have been able to improve supply chain management, strengthen market relationships, and optimize decision-making through the combination of artificial intelligence (AI) and big data. This study examines how AI and Big Data are used in government programs for agricultural marketing, focusing on how technologies affect resource allocation, price forecasting, and policy making. Big Data analytics makes it possible to gather and analyze enormous volumes of agricultural data, such as economic developments, soil health, and variations in the weather. Farmers may make educated decisions about crop selection, storage, and sales by using AI-driven models that use this data to deliver real-time insights. Government schemes that use AI to improve transaction efficiency and lessen information asymmetry include India's e-NAM (National Agricultural Market). While AI-powered chat bots and mobile apps provide farmers with advising services, predictive analytics forecasts changes in supply and demand, which helps stabilize prices. Additionally, AI-powered remote sensing and satellite imagery support crop monitoring and catastrophe management by assuring prompt interventions. When used with artificial intelligence, block chain technology enhances supply chain traceability, minimizes fraud, and guarantees fair pricing. Issues like infrastructure deficiencies, digital literacy, and data privacy issues continue to exist, necessitating policy interventions for successful being adopted.

In addition to highlighting the necessity of inclusive digital policies to close the technological gap for small and marginal farmers, this article emphasizes the revolutionary potential of artificial intelligence (AI) and big data in government-led marketing for agriculture programs.