Developing an AI-enabled inventory and procurement systems for optimizing operational efficiency in informal supply chains across Africa

This comprehensive review examines the transformative potential of artificial intelligence in revolutionizing inventory management and procurement processes within Africa's informal supply chains. Through systematic analysis of existing literature, case studies, and technological implementations, we investigate how AI-driven systems can enhance operational efficiency, reduce costs, and improve supply chain resilience in challenging informal market environments. Our research methodology encompasses qualitative and quantitative analysis of implementation data, focusing on system performance, adoption barriers, and socioeconomic impacts. The research reveals that AI-enabled systems demonstrate significant potential for improving inventory optimization, demand forecasting, and procurement efficiency in informal supply chains through enhanced data analytics, predictive modeling, and automated decision-making capabilities. We address critical challenges including digital literacy gaps, infrastructure limitations, and cultural resistance to technological adoption, providing insights into effective implementation strategies and sustainable development approaches. The study presents a framework for AI integration in informal supply chains that considers both technological requirements and socioeconomic factors, incorporating emerging trends in mobile technology, blockchain integration, and collaborative platforms. This work contributes to the growing body of literature on digital transformation in developing economies by offering a comprehensive analysis of AI's role in creating more efficient, resilient, and inclusive supply chain systems across Africa.