Abstract: Artificial intelligence has become a crucial force in enabling entrepreneurial development, playing an increasingly important role in the chance of entrepreneurial opportunity discovering and value creating. Although the entrepreneurial field has gradually paid attention to artificial intelligence, the current research on artificial intelligence-enabled entrepreneurship is still fragmented and lacks systematic integration. This paper adopted the unsupervised machine learning methods, combined machine coding with manual coding, and used structure topic models to analyze 122 relevant literatures collected by Web of Science. This study sorted out the current research status from the aspects of the antecedents, scenarios, processes, results, theoretical perspectives, and tools and methods of AI-enabled entrepreneurship. This study found that the research on the driving mechanism of AI-enabled entrepreneurship needs to be further deepened, the research on scenario fields needs to be further enriched, the research on path mechanisms needs to be further explored, the research on dual impacts needs to be further discussed, the underlying logic needs to be further broken through, and the technical instruments need to be further integrated. On this basis, it proposed a future research framework and topics, and revealed that we should deepen the research on the driving force of AI-enabled entrepreneurship at the macro-, meso-, micro- and even cross-level levels, promote the research on the multi-scenario ecology of AIenabled entrepreneurship in regions, industries and fields, strengthen the research on the process path of AI-enabled entrepreneurship from a cross-level and dynamic perspective, pay full attention to the possible positive results of AI-enabled entrepreneurship, especially the negative impact, and further explore the unique theoretical system of AI-enabled entrepreneurship based on new practices, provide solid data, tools and methods to support the research on AI-enabled entrepreneurship. By combing through existing literature and constructing a future research framework, this paper will provide a guideline for enriching and deepening research on artificial intelligence-enabled entrepreneurship.

Key words: artificial intelligence (AI), machine learning, structural topic model, entrepreneurship