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This study adopts a theory elaboration approach to systematically review 148 peer-reviewed articles published between 2016 and 2025 on the integration of artificial intelligence (AI) in start-ups. Drawing on foundational theories such as the technology acceptance model, resource-based view (RBV), dynamic capabilities, and institutional theory, it develops a conceptual framework that highlights both opportunities and challenges associated with AI adoption. Opportunities include enhanced operational efficiency, innovation enablement, and improved decision making. Challenges involve regulatory complexity, ethical concerns, scalability issues, and limited resources. The study contributes theoretically by identifying emerging constructs and refining interconstruct relationships within AI-driven start-up ecosystems. It proposes a future research agenda calling for empirical validation of the framework across sectors and geographies. Practical implications are discussed for start-up founders, investors, and policy makers, emphasizing the need for strategic alignment, AI governance, and talent development to ensure responsible and sustainable integration of AI within entrepreneurial environments in start-ups.
Abbas et al. (Mon,) studied this question.