Narrow Artificial Intelligence, Supply Chain Resilience, and SMEs in Developing Countries: A Protocol for a Scoping Review

Supply chains are increasingly vulnerable to disruptions such as geopolitical conflicts, natural disasters, and cyberattacks, with small and medium-sized enterprises (SMEs) in developing economies particularly affected due to resource constraints. Narrow Artificial Intelligence (ANI), a specialised form of AI designed for specific tasks, offers opportunities to enhance supply chain resilience (SCR) through predictive analytics, greater agility, and faster recovery. However, significant gaps persist in understanding ANI adoption in relation to government support mechanisms, labour market dynamics, and cybersecurity challenges. This scoping review aims to map and synthesise evidence on ANI’s role in strengthening SCR among SMEs in developing countries, and to examine its contributions to agility, adaptability, transparency, and sustainable practices aligned with the Industry 5.0 transition. Following the JBI methodology and PRISMA-ScR guidelines, and employing the Population, Concept, and Context (PCC) framework, the review includes qualitative, quantitative, and mixed-methods studies. Searches will span seven major databases and grey literature sources, and two independent reviewers will conduct screening, data extraction, and thematic synthesis using Rayyan. The findings will identify trends, opportunities, and knowledge gaps to inform research agendas, policy development, and practical strategies for building resilient supply chains in emerging markets.