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Digital Transformation of Industry Through Using AI: A Bibliometric Analysis Approach

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  • Wadim Strielkowski

    (Cambridge Institute for Advanced Studies
    Prague Business School)

Abstract

This paper focuses on the theoretical literature overview and bibliometric network analysis of the recent trends in digital transformation and artificial intelligence (AI) in industry. This transformation is characterized by the adoption of digital technologies that reshape modern business processes, organizational strategies and approaches, the role of human capital in industry, as well as value creation. It is very well portrayed by the raising interest in these topics in the academic research literature: from just 2 papers published in 2018 to more than 200 papers in 2024 (according to the Web of Science (WoS), the world renown academic citation and abstract database). This paper identifies major themes, technological advancements, and future research directions based on text and bibliometric network analyses, including the network text and bibliographic data from the 550 papers selected from the WoS database using the keywords “digital transformation of industry” and “AI in industry”. Our main results highlight the progression from Industry 4.0 towards Industry 5.0 paradigms emphasizing human-centric, sustainable, as well as resilient approaches. It appears that topics such as Industry 4.0, digital twins, AI-enabled operational excellence, and supply chain optimization are already entrenched. At the same time, topics such as ethical AI usage, workforce development, and the integration of cutting-edge AI such as generative models are quite new and are still evolving. Our results might be of special importance for the relevant stakeholders, entrepreneurs and industry pioneers, as well as policymakers interested in the digital transformation of industry.

Suggested Citation

  • Wadim Strielkowski, 2025. "Digital Transformation of Industry Through Using AI: A Bibliometric Analysis Approach," Lecture Notes in Information Systems and Organization,, Springer.
    • Handle: RePEc:spr:lnichp:978-3-032-00118-4_2
    DOI: 10.1007/978-3-032-00118-4_2
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