Artificial Intelligence Adoption in Entrepreneurship and Digital Transformation: A Bibliometric–Thematic Review of Intellectual Structure and Emerging Frontiers

Abstract

This study examines the evolving intellectual structure of artificial intelligence (AI) adoption at the intersection of entrepreneurship and digital transformation. Using a hybrid bibliometric–thematic review design with VOSviewer software, the study analyzes 1085 Web of Science publications (2017–2026) selected through a screening protocol. Performance analysis and four types of science mapping—co-word analysis, term co-occurrence, co-authorship, and institutional/geographic networks—were employed to identify publication trajectories, influential contributors, and the conceptual architecture of the field. The findings reveal a pronounced J-curve in publication growth, with substantial acceleration after 2022. Five dominant thematic domains emerge: AI and ecosystem strategy, strategic management and dynamic capabilities, predictive analytics and SME applications, digital transformation and sustainability, and behavioral determinants of technology acceptance. The thematic synthesis suggests that AI adoption in entrepreneurial contexts is a multi-level organizational phenomenon shaped by capability development, institutional conditions, human–AI complementarity, and responsible governance. The review identifies a clear shift from predictive and technical applications toward strategic, human-centered, and sustainability-oriented perspectives. By integrating bibliometric evidence with interpretive thematic analysis, this study addresses literature fragmentation and develops a coherent future research agenda emphasizing longitudinal designs, cross-level theorization, contextual sensitivity, and ethical AI frameworks. The study provides a foundation for scholars, entrepreneurs, and policymakers seeking to understand AI’s role in sustainable competitive advantage.