Data-Driven Policymaking for Sustainable Agribusiness Development: An Analysis on Leveraging AI and Digital Technologies

Abstract

The global agricultural sector faces an unprecedented convergence of challenges: population growth, accelerating climate variability, and chronic food insecurity. Artificial intelligence (AI) and digital technologies have emerged as transformative instruments capable of reshaping agribusiness value chains and enabling evidence-based policymaking at scale. This paper examines how data-driven policymaking can advance sustainable agribusiness development in Nigeria—Africa's largest economy—with particular focus on how AI technologies proven in the United States, the Netherlands, Japan, and Australia can be directly replicated and adapted for the Nigerian context. Nigeria's agricultural sector, contributing 24.8 percent of GDP and employing over 70 percent of the rural population, stands at a critical inflection point characterized by profound dualities of latent potential and systematic underperformance. The paper maps specific replication pathways across six priority domains: satellite crop monitoring, AI-powered market intelligence, precision agriculture for smallholders, agricultural finance and index insurance, supply chain optimization, and national data infrastructure. Drawing on proven pilot programs already operational in Nigeria, the paper presents eight integrated, actionable policy recommendations spanning data infrastructure establishment, national governance frameworks, digital extension services, AI innovation funding, broadband connectivity, and evidence-based monitoring architecture. Together, these constitute a coherent digital transformation agenda capable of closing Nigeria's productivity gap and positioning the country as a continental leader in sustainable agribusiness development.