Background Artificial intelligence (AI) is transforming entrepreneurial ecosystems by reshaping business models, decision-making processes, and competitive dynamics. Entrepreneurs face significant organizational, technological, and regulatory challenges when integrating AI into their ventures. Methods A Systematic Literature Review (SLR) was conducted following PRISMA 2020 guidelines. Publications between 2020 and 2024 were retrieved from Scopus, Web of Science, Taylor & Francis, and SciELO. Using the CIMO framework, 721 records were identified. After screening and quality assessment (cutoff ≥7/10), 26 studies were included. Results Organizational culture, entrepreneurial mindset, and digital competencies strongly influence AI adoption. Automation and data analytics—particularly machine learning—are the most implemented strategies. Barriers include resistance to change, lack of AI skills, regulatory uncertainty, cybersecurity concerns, and ethical risks. Government innovation policies positively affect AI investment decisions. Conclusions Successful AI integration requires agile structures, continuous training, institutional collaboration, and supportive regulatory frameworks. Entrepreneurs embedding innovation and digital upskilling demonstrate greater adaptability and sustainability.
_Paredes et al. (Fri,) studied this question.