Artificial intelligence and entrepreneurial innovation: Mapping the intellectual structure of an emerging research field

Artificial intelligence (AI) has rapidly become a strategic force in entrepreneurship, innovation, and digital business transformation. Yet, the rapid growth of publications across management, information systems, and technology studies has made it difficult to identify the dominant themes and evolving knowledge structure of AI-enabled entrepreneurship research. This study addresses that challenge through a bibliometric analysis of Scopus-indexed journal articles published between 2015 and 2025. A PRISMA-based screening procedure was applied to retrieve and filter the dataset, resulting in 623 journal articles for final analysis. Keyword co-occurrence analysis and science mapping were conducted using VOSviewer to identify major thematic clusters, research hotspots, and temporal shifts in topic prominence. The results reveal four major clusters: AI-driven opportunity recognition, technological innovation and digital transformation, machine learning applications in business decision-making, and digital platforms with business model innovation. The overlay analysis further indicates a thematic shift from technically oriented AI topics toward ecosystem-, platform-, and business-model-oriented perspectives. This study contributes to the literature by providing a field-specific bibliometric mapping of AI-enabled entrepreneurship, clarifying its intellectual structure, and proposing a future research agenda centered on entrepreneurial cognition, human-AI collaboration, and digitally mediated innovation ecosystems.