Proceedings of the 70th International Academic Conference, Madrid

FROM TECHNOLOGY TO ORGANIZATION: IDENTIFYING THE KEY DETERMINANTS OF AI ADOPTION STAGES IN SLOVAK SMES USING THE TOE FRAMEWORK

DIANA PALLÉROVÁ, VLADIMÍR HOJDÍK

Abstract:

Artificial intelligence (AI) has become an important component of firm-level competitiveness, process automation, decision-making, and digital transformation initiatives. However, the extent of AI adoption varies considerably among small and medium-sized enterprises (SMEs), suggesting that successful implementation depends on multiple technological, organizational, and environmental conditions. This study aims to identify the key determinants that predict firms' progression toward higher stages of AI adoption using the Technology-Organization-Environment (TOE) framework. The study contributes to the literature by conceptualizing AI adoption as a five-stage ordinal process, ranging from non-adoption to organization-wide implementation, thereby capturing the gradual nature of AI diffusion rather than treating adoption as a binary outcome. The empirical analysis is based on survey data collected from 234 Slovak SMEs. Reliability analysis, descriptive statistics, Spearman correlation analysis, and ordinal logistic regression were employed to examine the relationships between TOE subfactors and AI adoption stage. The results indicate that organizational determinants play the most important role in explaining firms' progression toward more advanced stages of AI adoption. Specifically, top management support and AI strategy, employee skills and AI training, and resources, processes and incentives for AI adoption emerged as significant predictors. Among technological determinants, only perceived technological effectiveness and economic feasibility significantly increased the likelihood of higher AI adoption, while none of the environmental factors retained statistical significance in the multivariate model. The findings suggest that AI adoption in SMEs should be understood primarily as an organizational capability-building process rather than a purely technological decision. By incorporating different implementation stages into the empirical model, the study provides a more nuanced explanation of AI adoption dynamics and extends existing TOE-based research with a stage-oriented perspective. The findings also offer practical implications for managers and policymakers seeking to accelerate AI adoption in SMEs.

Keywords: Artificial intelligence adoption; SME; TOE framework; Organizational readiness; Digital transformation

DOI: 10.20472/IAC.2026.070.014

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