Quantitative analysis reveals analytical capabilities drive middle-management restructuring in EU enterprises, suggesting AI adoption alters management roles rather than directly displacing them.
This study examines whether the growing adoption of artificial intelligence (AI) technologies is associated with measurable organizational restructuring processes within enterprises across the European Union (EU).While existing research mainly focuses on the determinants and performance effects of AI adoption, the organizational consequences of AI integration remain insufficiently explored.To address this gap, the study develops a capability-based conceptual framework linking internal enterprise-level capabilities, AI adoption mechanisms, and organizational restructuring outcomes.The empirical analysis is based on comparative Eurostat datasets covering EU countries and includes indicators related to digital capabilities, organizational innovation, AI adoption, and middlemanagement employment structures.Methodologically, the study applies a two-stage quantitative approach combining K-means cluster analysis and linear regression analysis.The results reveal substantial heterogeneity among EU countries in terms of digital integration, organizational innovation, and AI adoption intensity.The findings further suggest that AI-driven organizational restructuring does not manifest itself through simple managerial displacement.Instead, enterprise analytical capabilitiesparticularly the diffusion of Business Intelligence (BI) softwareare positively associated with changes in middle-management structures in more digitally advanced organizational environments.The study contributes to the literature by shifting attention from AI adoption itself toward its organizational implications and by providing an indirect quantitative assessment of AI-driven corporate organizational restructuring within the EU.
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Pan et al. (2026) studied this question.
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