Navigating Digital Transformation: Sociological and Educational Factors in Corporate AI Strategy Adoption

Shijie Chen and Haoer Chen
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Shijie Chen: Seoul School of Integrated Sciences & Technologies, South Korea
Haoer Chen: Xi'an University of Finance and Economics, China

European Journal of Social Science Education and Research, 2026, vol. 13, issue 3, 16-39

Abstract: To address the practical challenge of the disconnect between AI strategy implementation and performance outcomes in enterprises, this study focuses on the three-dimensional execution mechanism encompassing "resourcesprocess-culture," examining its mediating role between AI strategies and corporate performance, as well as the moderating effects of firm size and industry characteristics. Data were collected via random sampling using the Wenjuanxing online survey platform, supplemented by a 12-month longitudinal case tracking study. Empirical analysis employed structural equation modeling, grouped regression, and interaction term testing. Results demonstrate that the three-dimensional execution mechanism fully mediates the relationship between AI strategies and corporate performance, with resource allocation playing the most significant mediating role. Firm size positively moderates the performance effect of the execution mechanism, with large firms exhibiting significantly better implementation outcomes than small and medium-sized enterprises. Industry characteristics exhibit heterogeneity: technology-intensive industries show stronger positive impacts of the execution mechanism compared to non-technology-intensive sectors. Differentiation in implementation pathways reveals adaptability— technology-intensive firms benefit from a "resource priority or lightweight resources plus cultural guidance" approach, while non-technology-intensive firms are better suited for a "culture priority plus lightweight processes" model. This study evaluates AI strategy implementation primarily through organizational financial and innovation performance indicators. Although these metrics serve as organizational-level proxies for implementation effectiveness, they do not directly measure employee-level social outcomes, such as workplace learning, well-being, psychological safety, re-skilling, or perceived equity; therefore, the social implications discussed in this study should be interpreted within this scope.

Keywords: AI adoption; Organizational learning; Digital transformation; Workplace sociology; Socio-technical systems; Workplace equity (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:eur:ejserj:476

DOI: 10.26417/mck5nml6

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