The development of artificial intelligence (AI) has brought fundamental changes to the entrepreneurial process, particularly in the stage of entrepreneurial opportunity recognition. Although the literature on AI and entrepreneurship continues to grow, an integrated understanding of how AI transforms the opportunity recognition process remains fragmented. Therefore, this study aims to systematically examine the role of AI in transforming entrepreneurial opportunity recognition through a Systematic Literature Review (SLR) approach. This research follows the PRISMA guidelines by analyzing 40 reputable journal articles published between 2015 and 2025 and sourced from the Scopus, Web of Science, and Google Scholar databases. The analysis employs a thematic synthesis approach to identify key patterns, mechanisms, and implications of AI integration in opportunity recognition. The synthesis results reveal four main themes: (1) AI as an enabler in detecting patterns and latent opportunities, (2) the transformation of entrepreneurial cognition toward a human–machine hybrid model, (3) enhanced opportunity validation and reduced uncertainty through predictive analytics, and (4) ethical challenges and risks of algorithmic dependence. This study contributes theoretically by expanding the understanding of opportunity recognition in the context of digital entrepreneurship and practically by providing implications for entrepreneurs and policymakers in managing the strategic and responsible use of AI.
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