<![CDATA[This study performs a bibliometric and scientometric evaluation of worldwide research on Artificial Intelligence (AI) in Digital Business utilizing Scopus data from 2020 to 2025. Utilizing VOSviewer and Bibliometrix, we delineate keyword co-occurrence, author collaboration, and institutional networks to discern prevailing clusters and emerging fronts. Results indicate that digital business, digital transformation, and AI capabilities are fundamental themes, whereas digital ecosystems, sustainability, responsible and trustworthy innovation, and governance-focused analytics are emerging trends. Network analysis indicates strong European connections spearheaded by Georg-August-Universität Göttingen, the University of St. Gallen, and KU Leuven, alongside expanding transatlantic relationships and collaborative multi-institutional groups. We theoretically combine the Resource-Based View and Dynamic Capabilities, positing that data assets, algorithms, and human–AI routines are strategic resources whose orchestration facilitates perceiving, seizing, and reconfiguring amid chaotic changes. The methodological integration of performance metrics with scientific mapping reveals the structure, maturity, and interdisciplinary knowledge connections within fields such as information systems, management, and computer science. The study provides managerial guidance for aligning technical innovation with governance and sustainability: invest in interoperable data infrastructure, implement responsible AI safeguards, cultivate ambidextrous teams, and assess value creation beyond productivity, focusing on resilience and environmental, social, and ethical outcomes. Policy implications encompass incentives for open standards, development of skills pipelines, and facilitation of cross-border collaboration. Limitations encompass exclusive Scopus coverage, a predominance of English language, and rapidly evolving terminology; nonetheless, triangulated approaches reduce bias and offer a timely guide for researchers and decision-makers. Subsequent research should corroborate these findings using longitudinal datasets.]]>
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