Fostering Agricultural Transformation in Zambia: Implementing Artificial Intelligence Solutions for Sustainable Farming

Abstract

This paper explores the transformative potential of Artificial Intelligence (AI) in addressing persistent challenges within Zambia's agricultural sector, which employs approximately 54% of the population and contributes significantly to the national economy. Despite this importance, agriculture remains hindered by low productivity, erratic rainfall, soil degradation, and limited adoption of modern technologies. AI applications—including crop disease detection, precision farming, weather prediction for climate adaptation, and optimization of water resources—have shown significant promise in improving agricultural productivity and resilience. This paper adopts a mixed-methods approach that integrates field observations, interviews with smallholder farmers, extension officers, and quantitative analysis of secondary data. Findings indicate that AI adoption can boost yields, reduce losses, and support climate resilience when adapted to local contexts. However, barriers such as limited rural connectivity, digital illiteracy, and cost of deployment remain. The paper recommends stronger partnerships between government, universities, and the private sector to foster localized AI solutions. The study concludes that AI can be a key enabler in Zambia’s agricultural transformation when embedded within inclusive, farmer-centered frameworks.