Usage of Artificial Intelligence and Investment Avenues in Indian Agriculture: An Overview

Abstract

Indian agriculture transitioned from analogue systems toward digitally enabled ecosystems, with Artificial Intelligence (AI) and allied technologies—remote sensing, drones, IoT, machine learning, and decision-support systems—emerging as critical enablers of crop planning, resource optimisation, and risk management. Policy initiatives such as the Digital Agriculture Mission, Agri-Stack, and Krishi DSS laid the foundation for a digital public infrastructure (DPI), while regulatory reforms like Drone Rules liberalisation and the Kisan Drone scheme catalysed service-led adoption models through FPOs and Custom Hiring Centres. On-ground applications demonstrated measurable benefits: fertiliser and pesticide savings of 10–20%, water savings of up to 30%, and yield uplifts of 5–15% in pilot crops. Parallelly, investment avenues expanded significantly. Institutional agricultural credit touched a historic ₹25.1 lakh crore in FY 2023–24, though skewed towards southern states. Kisan Credit Card borrowings rose sharply, and collateral-free lending limits were enhanced to support smallholders. Venture funding in agri-tech, however, followed a boom-and-bust cycle, peaking at $802 million in 2022 before declining by 78% in 2023, reflecting investor caution. Public investment under PMKSY and RKVY bolstered infrastructure with mega food parks, cold chains, processing clusters, and direct support to more than 1,700 agri-startups.
Despite these advances, structural challenges persist: fragmented landholdings, poor digital literacy, limited rural connectivity, and gaps in data quality hinder AI scaling. The next phase (2025–2030) will hinge on completing digital registries, strengthening model marketplaces, enabling outcome-linked finance, and upgrading value chains. The period underscores a dual narrative—investment-led growth and technology adoption—tempered by systemic constraints.