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Divergent AI Transformation: China and U.S. Perspectives

Author(s)

Shengchang Zhang1, Qianyu Zhang2,*, Fred Zhang3

Affiliation(s)

1School of Business Administration, Baise University, Baise, Guangxi, China 2Derun Campus of Shandong Experimental High School, Jinan, Shandong, China 3PMS, Pleasanton, California, USA *Corresponding Author

Abstract

This study explores the divergent trajectories of AI-driven digital transformation in enterprises across China and the United States. Employing a comprehensive methodology that integrates a literature review, case analysis, and institutional framework evaluation, the research examines five critical dimensions: institutional frameworks, corporate strategic structures, data infrastructure ecosystems, talent development models, and innovation collaboration networks. Findings indicate that U.S. enterprises prioritize technology-driven innovation and market responsiveness, while Chinese firms benefit from strategic coordination and large-scale implementation, and large-scale deployment. The study underscores the pivotal role of institutional environments in shaping AI adoption patterns and offers strategic insights for global managers pursuing context-specific transformation, as well as for stakeholders aiming to foster effective cross-border AI collaboration.

Keywords

AI; Digital Transformation; Sino-U.S. Comparison; Corporate Strategy; Innovation Ecosystem

References

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