While the application of Artificial Intelligence in Finance has a long tradition, its potential in Entrepreneurship has been intensively explored only recently. In this context, Entrepreneurial Finance is a particularly fertile ground for future Artificial Intelligence proliferation. To support the latter, the study provides a bibliometric review of Artificial Intelligence applications in (1) entrepreneurial finance literature, and (2) corporate finance literature with implications for Entrepreneurship. Rigorous search and screening procedures of the scientific database Web of Science Core Collection resulted in the identification of 1890 relevant journal articles subjected to analysis. The bibliometric analysis gives a rich insight into the knowledge field's conceptual, intellectual, and social structure, indicating nascent and underdeveloped research directions. As far as we were able to identify, this is the first study to map and bibliometrically analyze the academic field concerning the relationship between Artificial Intelligence, Entrepreneurship, and Finance, and the first review that deals with Artificial Intelligence methods in Entrepreneurship. According to the results, Artificial Neural Network, Deep Neural Network and Support Vector Machine are highly represented in almost all identified topic niches. At the same time, applying Topic Modeling, Fuzzy Neural Network and Growing Hierarchical Self-organizing Map is quite rare. As an element of the research, and before final remarks, the article deals as well with a discussion of certain gaps in the relationship between Computer Science and Economics. These gaps do represent problems in the application of Artificial Intelligence in Economic Science. As a way to at least in part remedy this situation, the foundational paradigm and the bespoke demonstration of the Monte Carlo randomized algorithm are presented.

人工智能在金融领域的应用历史悠久，而在创业领域的潜力则是最近才被广泛探索的。本研究通过文献计量分析探讨了人工智能在创业金融和企业金融领域的应用，并展示了知识领域的概念、智力和社会结构，指出了尚未充分开发的研究方向。结果显示，在几乎所有的识别的主题领域中，人工神经网络、深度神经网络和支持向量机得以广泛应用，而主题建模、模糊神经网络和分层自组织映射则较少使用。此外，本文还探讨了计算机科学和经济学之间的某些差距，并介绍了蒙特卡洛随机算法的基本范式和具体示例，以解决这一问题。

创业金融中的人工智能：知识结构与基础算法范式