Högskolan i Skövde

This study explores how small and medium-sized businesses (SMEs) use artificial intelligence (AI) to make their supply chain more resilient, especially when facing disruptions.

I interviewed seven managers of SMEs in Ghana and the UK in the logistics, retail, and manufacturing sectors. These findings revealed how they implemented AI despite facing constraints. The findings show that SMEs are using AI in creative ways. There is an improved accuracy in predicting customer demand, reducing waste, and cutting emergency purchases.

All the SMEs used similar approaches, that is, starting small with pilot projects by focusing on problems that directly cost them money, and gradually building their capabilities over time. They faced common challenges, including poor data quality, limited budgets, lack of technical expertise, and resistance from employees who were worried about possible job losses. SMEs in Ghana faced infrastructure challenges and needed external funding, while UK businesses mainly struggled with expertise gaps.

The research adds to theoretical understanding by extending the Resilience Theory, Resource-Based View and Dynamic Capabilities Theory, which demonstrates how SMEs with limited resources can achieve resilience capabilities typically associated with larger enterprises through strategic AI implementation. The human-AI collaborative approach challenges existing frameworks usually focused on automation. Thereby, suggesting a new shift for technology adoption in resource-constrained environment. These findings have important implications for understanding how AI technologies can open up access to advanced supply chain resilience capabilities.