Exploring Epistemological Perspectives on AI Integration in Entrepreneurial Data-Driven Decision-Making: Rationalist, Empirical, and Constructivist Approaches

This article investigates the influence of epistemological theories on the integration of artificial intelligence (AI) in entrepreneurial decision-making. By examining rationalism, empiricism, and constructivism, the study explores how these philosophical frameworks shape the development and application of AI technologies within entrepreneurship. Rationalist approaches emphasize logic-based AI, rule-based systems, and algorithmic decision-making, underscoring the role of formal logic and structured reasoning. Empirical methods highlight the importance of data collection, machine learning, and evidence-based strategies, focusing on data-driven approaches to enhance AI performance. Constructivist theory emphasizes learning algorithms, adaptive systems, and user-centered design, fostering innovation and adaptability in AI-driven entrepreneurial strategies. This comprehensive review provides insights into the practical implications for entrepreneurs and AI developers, emphasizing the creation of robust, reliable, and adaptable AI systems. The article also discusses future research directions, suggesting a deeper integration of ethical considerations and user-centered design principles in AI development. By grounding AI applications in solid epistemological foundations, this study aims to contribute to the fields of entrepreneurship, AI, policy, and philosophy, highlighting the critical role of knowledge frameworks in driving technological innovation and sustainable business growth.