TY - JOUR
T1 - Digital Inequality in Intelligent Agriculture: A Theory of Data Access, Infrastructure Gaps, Platform Dependence, and Uneven Value Capture
AU - Samuel Boateng
AU - Kwesi Mensah
JF - Journal of Intelligent Agriculture and Food Systems
Y1 - 2026
VL - 5
IS - 1
SP - 42
N2 - Intelligent agriculture increasingly relies on data-intensive systems, including sensors, connectivity, decision-support tools, automation, platforms, machine learning, and analytics. These systems are often presented as pathways toward more productive, efficient, resilient, and sustainable farming. Yet their social effects depend on how access, control, capability, risk, and value are distributed across agricultural actors. The central problem addressed in this article is that intelligent agriculture can deepen inequality when digital systems are unevenly organised. Farmers and rural actors may face different levels of access to infrastructure, data, technical support, platform services, financial capacity, and bargaining power. As a result, the benefits of digitalisation may accumulate among actors already positioned to use, govern, and monetise data-driven systems. This article develops a theory of digital inequality in intelligent agriculture. The theory explains how data access, infrastructure gaps, platform dependence, and uneven value capture interact to shape distributional outcomes. It treats inequality not as a side effect of incomplete adoption but as a process produced through socio-technical relations. The approach integrates scholarship on digital agriculture, rural digital divides, agricultural platforms, farmer capability, data governance, infrastructure inequality, responsible innovation, and value distribution. Rather than treating smart farming as a neutral technological transition, the article develops constructs, mechanisms, relationships, boundary conditions, and propositions. The aim is to explain how digital agricultural systems can reproduce, intensify, or reduce inequality.The proposed theory argues that digital inequality in intelligent agriculture emerges through linked pathways of data exclusion, infrastructure disadvantage, capability constraint, platform control, and value appropriation. These pathways influence who can participate in intelligent agriculture, who becomes dependent on digital intermediaries, who bears risks, and who captures benefits. The article concludes that intelligent agriculture should be evaluated by its distributional consequences as well as its technical performance.
UR - https://airpublications.com/l615043708
ER -