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Do Bulgarian SMEs Differ from Their International Peers in Adoption of AI?

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  • Ma Lingling

    (Sofia University St.Kliment Ohridski, Sofia, Bulgaria)

Abstract

Artificial Intelligence (AI) technology as a disruptive technology of the 21st century, is leading an exceptionally profound technological revolution on a global scale. Existing studies indicate that AI adoption is a complex task compared to previous information technology revolution. The paper explores the adoption of AI technologies by Bulgarian Small and Medium-sized Enterprises (SMEs) in comparison to their international peers. Through a scoping literature review and empirical data analysis, this study aims to identify unique challenges, opportunities, and trends in AI adoption among Bulgarian SMEs. Specifically, this study founded in theory of Technological-Organizational-Environmental (TOE) framework and collected empirical data through a designed questionnaire. The survey distributed via social media and professional network. Through this approach, 140 responses were received from 16 countries, with 108 were fully filled. Moreover, factor analysis and variables correlations and liner correlated analysis ran for identifying factors leading to AI adoption in various countries. The findings reveal there is statistically significant difference in AI understanding and organizational readiness between two samples and Bulgarian companies demonstrated a higher level in this regards. Moreover, they exhibit diverse levels of AI adoption across different applications. Additionally, AI adoption is associated with the understanding of AI, organizations’ preparedness and competitive environment, and innovation. The paper concludes by suggesting strategies for enhancing AI adoption among Bulgarian SMEs to foster innovation and competitiveness.

Suggested Citation

  • Ma Lingling, 2025. "Do Bulgarian SMEs Differ from Their International Peers in Adoption of AI?," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 19(1), pages 3400-3410.
  • Handle: RePEc:vrs:poicbe:v:19:y:2025:i:1:p:3400-3410:n:1028
    DOI: 10.2478/picbe-2025-0259
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