The Mediating Role of Organizational and Environmental Context in the Adoption Intention of Artificial Intelligence: A Higher-Order Double Mediation Analysis

Artificial intelligence (AI) adoption is increasingly viewed as a driver of business competitiveness, yet firms in emerging economies face structural barriers that adoption models built for advanced economies rarely capture. This study aims to examine how organizational context (OC) and environmental context (EC) mediate the relationship between technological context (TC) and firms’ intention to adopt AI. Grounded in the Technology–Organization–Environment (TOE) framework and Diffusion of Innovation (DOI) theory, the study surveyed 302 Colombian companies across multiple economic sectors and analyzed the data using partial least squares structural equation modeling (PLS-SEM) with a higher-order, sequential double-mediation specification. The results show that, in the main specification, technological context has no significant direct effect on AI adoption intention; instead, its influence is channeled through environmental and organizational context in a sequential mediation pathway. This finding indicates that technological readiness alone is insufficient to drive adoption in the study’s context, and that environmental pressures must first be internalized through organizational capabilities before firms translate technological potential into adoption intention. The study contributes to TOE theory by reframing technology-adoption relationships as context-dependent rather than direct, and offers evidence-based implications for managers and policymakers seeking to promote AI adoption in resource-constrained, emerging-economy settings.