Artificial Intelligence Capabilities and Digital Marketing Performanceamong Somali Businesses

Abstract

Artificial intelligence (AI) can support personalization, campaign automation, customer analytics, and content generation, but evidence from resource-constrained markets remains limited. Drawing on the technology-organization-environment framework and the resource- based view, this study examines associations between four AI marketing capabilities—AI- enabled personalization, marketing automation, AI-driven analytics, and generative AI—and digital marketing performance among Somali businesses. It also tests whether organizational AI readiness moderates the relationship between an overall AI-capability measure and performance. A cross-sectional survey produced 327 usable responses from marketing managers, business owners, and marketing specialists. Multi-item measures were assessed for reliability and convergent and discriminant validity. Hierarchical moderated regression showed that the main-effects model explained 40.3% of the variance in digital marketing performance. Automation had the largest standardized association with performance (β = .257, p < .001), followed by personalization (β = .200, p < .001), generative AI (β = .177, p = .001), and analytics (β = .149, p = .001). The capability-by-readiness interaction was also significant (b = .283, p < .001), increasing explained variance by 2.7 percentage points. These cross-sectional findings show associations rather than causal effects. The study provides an initial empirical benchmark for AI-enabled marketing in Somalia. The results suggest that firms may gain greater marketing value when AI-tool adoption is accompanied by technical skills, digital infrastructure, management commitment, and appropriate governance.