Artificial Intelligence in entrepreneurship: Mapping a fragmented field and advancing a cognitive research agenda
Catalina D. Retamal-Saavedra et al.
Abstract
This study offers a systematic and theory-informed integrative synthesis of research at the intersection of artificial intelligence (AI) and entrepreneurship. Although interest in this domain has expanded rapidly, existing research remains fragmented, technology centered, and weakly connected to theories of entrepreneurial decision-making. To address this gap, the study adopts a hybrid review design that combines a systematic literature review with bibliometric co-word analysis and thematic synthesis. Based on 372 articles indexed in the Web of Science (WoS) Core Collection (2010–2025), the analysis maps the intellectual structure, thematic landscape, and temporal evolution of AI–entrepreneurship research. Four thematic quadrants are identified, reflecting core applications, transversal foundations, isolated specializations, and peripheral themes. The synthesis shows that AI is largely conceptualized as a functional input, while cognitive and behavioral dimensions of entrepreneurial judgment remain marginal. Building on these insights, the article proposes a cognitively informed research agenda to guide future work.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.