Prospects and challenges of artificial intelligence for food security sustainability in Africa: case of South Africa and Nigeria

Artificial intelligence (AI) has increasingly emerged as a transformative technology with the potential to reshape agricultural systems and strengthen food security sustainability in Africa. It is against this backdrop that this study examines the prospects and challenges of AI for food security sustainability in Nigeria and South Africa, adopting a qualitative comparative research design and drawing on secondary sources of data. The analysis is anchored in embedded liberalism theory and agro-ecological theory, which provide complementary perspectives for examining the institutional, socioeconomic, technological, and ecological conditions that shape the sustainable application of AI in agriculture. Findings indicate that large agricultural yield gaps and the predominance of smallholder farming in Nigeria, alongside South Africa’s relatively advanced digital infrastructure, commercial agricultural systems, and innovation ecosystem, present significant opportunities for AI-enabled improvements in agricultural productivity, resilience, and resource efficiency. However, these prospects are moderated by context-specific challenges. Nigeria faces persistent infrastructural, institutional, and technological constraints, while South Africa’s principal challenge lies in inequality-driven exclusion and uneven access to technological benefits. The study therefore argues that AI can contribute meaningfully to food security sustainability when embedded within inclusive institutional arrangements, sustainable agricultural practices, ecological conservation, and context-sensitive governance frameworks.