The pervasive integration of artificial intelligence (AI) is fundamentally reshaping societal and business landscapes, presenting both significant opportunities and challenges, particularly within the entrepreneurial sphere. AI’s potential to alter venture conception, development, scaling, market entry, and competitive dynamics necessitates a re-evaluation of traditional entrepreneurship theories. As a key enabling technology, AI revolutionises core entrepreneurial processes, from ideation to market expansion, fostering novel forms of value creation and opportunity identification. However, despite acknowledging the influence of digital technologies, a comprehensive understanding of specific research trends concerning AI’s role, especially following the widespread adoption of generative AI tools like ChatGPT, remains underdeveloped. This study addresses this gap through a bibliometric systematic literature review. Utilising the Web of Science database and the “bibliometrix” R-package, we employ thematic evolution analysis to map the trajectory of research topics at the intersection of AI and entrepreneurship, specifically comparing the pre- and post-ChatGPT periods. We aim to visualise the field’s structure, identify influential contributions, and track thematic shifts. Anticipated findings include the emergence of research streams focused on generative AI’s impact on venture creation, ethical considerations, evolving decision-making processes, and the new skills required for AI-driven entrepreneurship. This analysis seeks to provide practical insights for entrepreneurs leveraging AI tools and highlight knowledge gaps and future research directions for academics, ultimately contributing to a deeper understanding of how AI is shaping the future of entrepreneurship.