This study presents a bibliometric analysis complemented by a qualitative examination to map the scientific evolution, intellectual structure, and thematic development of research on artificial intelligence (AI) in the digital transformation of value chains within the Industry 4.0 framework. The analysis includes 454 articles indexed in Scopus and Web of Science, retrieved for the 2015–2025 search window (with eligible publications observed from 2018 onward) and uses R (version 4.4.2) and VOSviewer (version 1.6.20). Guided by three research questions, the study examines (i) the temporal, geographical, and journal-level structure of scientific production; (ii) the dominant and emerging thematic structures of the field; and (iii) how highly cited studies contextualize the bibliometric patterns and reveal research gaps. The results show sustained growth in scientific output, with a marked increase after 2020. Publication growth after 2020 coincided with the COVID-19 pandemic period; however, this descriptive bibliometric analysis does not establish a causal relationship. The co-occurrence analysis identifies major themes related to digital transformation and automation, intelligent supply chains and logistics, and sustainability and value creation. The qualitative analysis of highly cited studies further highlights Industry 5.0, circular economy, digital twins, cybersecurity, digital health, technological convergence, and supply chain resilience. Overall, the findings indicate that AI is increasingly embedded in the technical, organizational, and strategic transformation of value chains. At the same time, the literature remains uneven across regions and underdeveloped in areas such as cybersecurity, context-specific digital maturity, environmental and ethical implications, and evidence from emerging economies. These results provide an integrated research agenda for future studies on sustainable and human-centered digital transformation.
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Sánchez-Villacrés et al. (2026) studied this question.
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