Harnessing Artificial Intelligence in Local Governance for Sustainable Food System Transformation in South Africa: A Review

The intersection of Artificial Intelligence (AI) and local governance represents a powerful frontier for attaining sustainable food systems and addressing the complex challenges of food security, agricultural productivity, and environmental sustainability. Despite growing interest in AI applications within agriculture, research examining the integration of AI into local governance frameworks remains limited, particularly regarding ethical implementation, institutional readiness and practical adoption in developing countries. Focusing on South Africa, this article examines the role of AI in strengthening local governance, identifies the major challenges faced by local governments in supporting food system actors, and explores how AI-driven solutions can enhance governance capacity to promote sustainable, inclusive, and resilient food systems. The article is underpinned by a systematic literature review of 61 peer-reviewed articles retrieved from the Scopus database using the search terms ‘local governance’ AND ‘food system’ OR ‘agriculture’ OR ‘agribusiness’ OR ‘agri-business’ OR ‘farm’ AND ‘South Africa’. This review was complemented by a narrative analysis of 17 documents from the grey literature, including policy re-ports, government publications, and institutional documents, to provide broader contextual insights and capture emerging developments not yet reflected in academic literature. The findings reveal that local governments face several interconnected challenges, including fragmented policy frameworks, limited institutional capacity, high implementation costs, low digital literacy among smallholder farmers, inadequate digital infrastructure, and a shortage of locally relevant, high-quality data for informed decision-making. To address these constraints, the study recommends leveraging AI-driven solutions to improve resource management, strengthen evidence-based policy making, optimize agricultural production, and enhance coordination among food system stakeholders. Future research should move beyond the current emphasis on AI's potential toward practical implementation and long-term resilience by prioritizing ethical data governance, reducing the digital divide, developing context-specific AI tools for smallholder farmers, and supporting urban food security initiatives across South Africa.