Artificial Intelligence Adoption and Financial Decision-Making Quality among SMEs in Freetown, Sierra Leone: The Moderating Role of Digital Capability

This study investigates the impact of artificial intelligence (AI) adoption on financial decision-making quality (FDMQ) among small and medium enterprises (SMEs) in Freetown, Sierra Leone. It examines the moderating role of digital capability. The study used a quantitative, cross-sectional survey design with a sample of 250 owner-managers and finance officers from SMEs in formal and semi-formal business clusters in Freetown, based on the Technology–Organization–Environment (TOE) framework and Resource-Based View (RBV). The data were analyzed using SPSS with descriptive statistics, correlation analysis, and hierarchical moderated multiple regression. Findings showed that AI adoption (β = .573, p .001) and digital capability (β = .283, p .001) were significant, positive predictors of FDMQ. The AI adoption–FDMQ relationship was also significantly moderated by digital capability (β = .195, ΔR² = .035, p .001). Simple slopes analysis showed that the effect of AI adoption was more than doubled when digital capability increased from low to high. AI adoption enhances SME financial decision-making, but its impact relies on supporting digital capabilities. The study builds on the TOE and RBV frameworks in an under-researched West African context. It emphasizes the importance of integrating AI provision with digital capability development. Findings suggest associations, not causal or broadly generalizable effects, because of the cross-sectional, self-reported design and the Freetown sample.