<p>Internet of Things (IoT) and Artificial Intelligence (AI) techniques have proven to be promising tools for enhancing the agricultural value chain. Despite the cassava crop being a staple food in Rwanda, technology adoption along its value chain is challenging. This study employs principal component analysis (PCA) and cluster analysis (CA) to examine the Key Factors Influencing IoT Adoption in the Cassava Value Chain. A structured questionnaire was administered to survey four districts: Ruhango, Nyanza, Bugesera, and Kayonza. The questionnaire covered six main areas: quality monitoring systems, safety controls, challenges across the value chain, technologies used, critical factors for improvement, and cassava management, sampling 202 stakeholders. Data were analyzed using Principal Components Analysis, with the main variables grouped through cluster analysis. The suggested approaches for IoT adoption strategies were compared using Tukey’s means comparison test and ranked with Wilcoxon’s rank test at a 5% significance level, using R Studio software. Results indicated that the presence of young stakeholders at the processing level, 4G cellular network coverage in rural areas, and the Kinazi Cassava Plant in Ruhango are significant strengths (more than 96%) for IoT adoption. Over 80% of stakeholders recognize that integrating IoT and artificial intelligence can improve precision farming in the cassava value chain, highlighting that investing in farmer training and monitoring technology is a key strategy for IoT adoption in Rwanda. These findings emphasize the potential of IoT to transform the cassava value chain in Rwanda and demonstrate the need for targeted interventions to address existing challenges.</p>