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The social impact of the digital revolution has been significant, affecting various aspects of daily life and work patterns (Makridakis, 2017) and making digitalization an important element in both economy and society (Peng & Tao, 2022). Technology is a crucial tool (Cheng et al., 2021) and is especially important for companies wishing to optimize their processes and strategies (Bui & Lo, 2022). Moreover, digitalization is useful both for mature companies with established business models facing a paradigm shift (Mithas et al. 2013) and for business ideas that need to establish themselves in the market. In recent years there has been great uncertainty in the international environment, with the result that the relationship between sustainability and digitalization has received much scholarly attention from authors such as Nyagadza (2022). This is because, on many occasions, the demands of business sustainability force organizations to seek the creation of value and structural changes in order to survive over time, adapt, and continue to satisfy the needs of society.
Entrepreneurship is a trend topic (Indrianti et al., 2020), and authors such as Audretsch and Moog (2022) argue that it deserves priority because it is linked to some of today’s economic and social problems. Tools such as Artificial Intelligence (AI) acquire special relevance in the digitalization of organizations, given the need for entrepreneurs to continuously adapt and keep abreast of new developments (Kraus et al. 2018). Thus, AI has been driven by the continuous changes in the market and the increasing needs of a growing population. The information technology (IoT) revolution has contributed significantly to the momentum of AI technology and to the interest shown by business and government leaders (Zhang & Lu, 2021). However, little has been written specifically on the link between entrepreneurship and AI (Popkova & Sergi, 2020; Dubey et al., 2020), despite authors such as Obschonka & Audretsch (2019) pointing out that the introduction of AI in entrepreneurship ushers in a new era.
Among other systematic literature reviews, it is worth highlighting Giuggioli & Pellegrini (2022), who point out the benefits of AI in entrepreneurial development. Our research, however, not only focuses on so-far absent semantic analysis but also continues and extends the analysis of the last two years, which is especially relevant due to the digital boost that followed the Covid-19 situation. On the other hand, Di Vaio et al. (2020) analyze the literature on AI and business models. In recent years, literature reviews have looked at the links between various topics, including education (Tahiru, 2021); health (Shah & Chircu, 2018); public administration (Reis et al., 2019); and consumer behavior (Mariani et al., 2022). It is the lack of existing systematic literature reviews about the role of AI in entrepreneurship that makes the present study valuable.
In the present study, the following research questions have been answered:
RQ1: How has the intersection between AI and entrepreneurship evolved?
RQ2: Who are the main authors in the field, and how do they relate to each other?
RQ3: What are the main linked research topics?
RQ4: How is it possible to leverage semantic analysis in a systematic literature review?
In order to answer these questions, this research proceeds as follows. Next, the key concepts of AI and entrepreneurship are analyzed. Then the methodology used is provided. Discussion of the results and an outline of the bibliometric results follow, including the semantic analysis of the scientific contributions. Finally, the main conclusions, the limitations encountered, and future lines of research are presented.