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A moderated model of artificial intelligence adoption in firms and its effects on their performance

Author

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  • Jing Chen

    (Wagner College)

  • Saeed Tajdini

    (Indiana University Southeast)

Abstract

Leveraging two prominent theories of technology adoption in firms, this study examines the organizational determinants of the adoption intensity of artificial intelligence (AI) and its effects on firms’ performance, under the moderating effects of technological turbulence. To conduct this study, a unique dataset was compiled via a survey of US-based managers involved with technology and AI adoption in high-tech goods and services, leading to 226 usable responses. Structural Equation Modeling was then applied to test the proposed model. The findings uncover the influence of technological, organizational, and environmental factors on the firms’ AI adoption intensity. Additionally, a positive correlation is observed between AI adoption intensity and firms' performance. Lastly, technological turbulence emerges as a crucial environmental factor moderating the effects of antecedents on AI. Given the feeble adoption of AI in firms despite its documented role in firms’ success, the current study can offer a road map to successfully implementing AI in firms and, thus, improving their performance.

Suggested Citation

  • Jing Chen & Saeed Tajdini, 2025. "A moderated model of artificial intelligence adoption in firms and its effects on their performance," Information Technology and Management, Springer, vol. 26(3), pages 407-419, September.
    • Handle: RePEc:spr:infotm:v:26:y:2025:i:3:d:10.1007_s10799-024-00422-5
    DOI: 10.1007/s10799-024-00422-5
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