Artificial Intelligence-Enabled Enterprise Digital Transformation: A Decade-Long Bibliometric Analysis of Knowledge Evolution, Research Frontiers, and Emerging Trends (2015–2025)
Keywords:
artificial intelligence, CiteSpace, enterprise digital transformation, business model innovation, smart supply chain, enterprise data governanceAbstract
Artificial Intelligence (AI) has emerged as a fundamental engine reshaping modern business ecosystems, driving enterprise digital transformation (EDT) from basic operational automation to dynamic business model innovation and strategic value co-creation. Although the literature on corporate digitalization is vast, the specific intellectual architecture, thematic convergence, and dynamic evolutionary pathways of AI-empowered enterprise transformation remain dispersed across management, computer science, and information systems literature. This study presents a comprehensive scientometric analysis of 312 high-impact publications retrieved from the Web of Science Core Collection (2015–2025). Leveraging CiteSpace 7.0.1 Advanced, we map global scientific collaboration networks, keyword co-occurrence topologies, thematic cluster structures, timeline progressions, and strong citation bursts. The empirical findings reveal an explosive publication expansion starting in 2022, with China and the United States serving as structural central hubs in global knowledge diffusion. Keyword clustering uncovers six core domain fronts: Smart Industrial IoT & Supply Chain Integration, Generative AI & Business Model Innovation, Enterprise Data Governance & Analytics, Intelligent Workflow Automation, Organizational Agility & Workforce Transformation, and AI Ethics & Strategic Risk Stewardship. Citation burst analytics highlight a pivotal paradigm transition from IT infrastructure optimization toward generative corporate workflows, agentic decision-support systems, and responsible AI governance. Based on these insights, a multi-tier strategic implementation matrix is formulated to assist executive leaders and corporate strategists in orchestrating sustainable AI-driven digital transformation.References
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Copyright (c) 2025 Kaizhou Qin, Mui Yee Cheok
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Published by University Tun Abdul Razak (UNIRAZAK)
