AI-Driven Decision-Making in Entrepreneurship: A Systematic Review and Research Agenda

Frame of the research. Artificial intelligence (AI) revolutionizes how entrepreneurs find opportunities and make strategic decisions. Nevertheless, business AI research is still fragmented. Thus, academic research needs a more comprehensive approach that brings existing knowledge and sets a clear direction for future research. Purpose of the paper. This study analyzes previous research on the application of AI in entrepreneurial scenarios to identify the main concerns at the nexus of entrepreneurship and AI. Methodology. We conducted a systematic literature review on 219 peer-reviewed articles published in English between 2010 and 2025. Using content analysis and thematic coding, we identify the most relevant research directions, theoretical perspectives, and gaps in the literature. Results. The study identified five main areas where AI and entrepreneurship intersect: (1) how AI promotes identifying new business opportunities; (2) how AI transforms business models; (3) how AI affects financial decisions; (4) how AI supports business development; and (5) how AI promotes cooperation within entrepreneurial ecosystems. Research limitations. First, only peer-reviewed papers published in English are used. Second, by focusing on the years 2010–2025, the analysis does not include any advancements that occurred after this time. Lastly, this research does not directly test AI’s impact on entrepreneurial success. Managerial implications. AI empowers entrepreneurs with better decision-making, scaling, and forecasting. From a managerial perspective, this study highlights the growing importance of integrating AI into entrepreneurial decision-making. Originality of the paper. We provide the AI-Driven Entrepreneurial Decision-Making framework to highlight how AI facilitates relevant entrepreneurial tasks including identifying opportunities, developing business models, and interacting with systems.