Introduction:

The integration of artificial intelligence (AI) and digital technologies into the agricultural sector represents a potentially transformative development for increasing productivity, optimizing resource use, and promoting sustainable practices. However, the diffusion of such innovations is far from uniform: significant disparities are emerging between small and large-scale farms, as well as between developed and marginal rural areas. This scenario raises serious concerns regarding existing structural inequalities and the risk of digital exclusion for a substantial portion of the farming population, particularly in disadvantaged contexts.

Methods:

This study presents a systematic review of recent empirical and conceptual literature (2019–2025), focusing on the adoption of smart farming technologies in sub-Saharan Africa. It analyzes eight key studies from Scopus-indexed sources, assessing infrastructure availability, economic barriers, and farmers' digital literacy through qualitative and quantitative approaches.

Results:

The findings reveal a substantial digital divide. Smallholder farmers report limited access to ICTs due to high costs, poor connectivity, and lack of technical support. In South Africa, 78.8% of surveyed farmers perceived digital tools as too expensive and 81% lacked the required skills (Bontsa et al. 2024). These barriers are compounded by perceptions of limited reliability and low trust in digital systems.

Conclusions:

While AI-driven farming promises increased efficiency, its benefits remain unequally distributed. Without targeted interventions, such as infrastructure development, affordable technology, and context-specific training, digital agriculture risks reinforcing existing inequalities. To ensure an inclusive agricultural transformation, policies must prioritize digital equity, particularly for marginalized rural producers.