AI-DRIVEN STAKEHOLDER MANAGEMENT STRATEGIES AND PROJECT SUSTAINABILITY IN AGRICULTURE AND FOOD SECURITY PROJECTS, KENYAN CONTEXT
Eunice Naliaka - Master of Project Management, Mykolas Romeris University, Vilnius
Prof. Dr. Asta Valackienė - Mykolas Romeris University, Vilnius
ABSTRACT
Agriculture and food security projects in Kenya continue to face sustainability challenges associated with fragmented stakeholder coordination, planning inefficiencies and suboptimal resource allocation. Although artificial intelligence (AI) is increasingly recognised as a potential enabler of data-driven project management, its application to stakeholder management and agricultural project sustainability in Kenya remains insufficiently institutionalised. This study examined the effects of four AI-driven stakeholder management strategies; machine learning, AI-based communication, AI mapping tools, and AI-driven monitoring and evaluation (M&E) on the sustainability of agriculture and food security projects in Kenya. A convergent parallel mixed-methods design was employed. Quantitative data were collected from 138 participants through stratified random sampling across key departments of the Agriculture and Food Authority (AFA), while qualitative evidence was obtained through semi-structured interviews with project and policy experts. Quantitative analysis using SPSS Version 23 indicated a strong joint relationship between the four AI dimensions and project sustainability (R = .826, R² = .682, F(4, 98) = 52.59, p < .001). AI-driven M&E (β = .389, p < .001) and machine learning (β = .322, p < .001) were the strongest reported predictors. Thematic analysis using NVivo 14 reinforced the quantitative findings through the themes of AI-enabled stakeholder visibility and real-time monitoring for sustainability decision-making. The findings indicate that AI can strengthen stakeholder coordination, resource-related decision-making, communication and monitoring within agricultural projects. The study contributes empirical evidence on AI-driven stakeholder management in the Kenyan agricultural context and supports greater institutionalisation of AI systems, staff capacity development and operational procedures for sustainable project delivery.