Entrepreneurship has long been associated with bold founders, disruptive startups, and stories of extraordinary success. Yet behind these narratives lies a deeper and increasingly influential academic discipline. Artificial intelligence (AI) has emerged as a critical focus for entrepreneurs, driving the development of AI-based startups to address challenges in various sectors. Despite increased innovation from data availability and supportive digitization legislation, some industries such as the healthcare industry remains resistant to disruptive technologies due to the strict regulations (Zahlan, et al., 2025). Entrepreneurship as a field of research has matured significantly over the past few decades, moving from anecdotal storytelling to rigorous theoretical and empirical investigation. What was once considered a niche topic within business schools has emerged as a vital domain that intersects economics, psychology, sociology, strategy, innovation, and public policy. The growing prominence of entrepreneurship research is not accidental. Economies worldwide are driven by innovation, technological change, and knowledge creation. Startups reshape industries, small firms fuel employment growth, and entrepreneurial thinking permeates organizations of all sizes. As a result, understanding entrepreneurship is no longer optional for scholars, policymakers, or practitioners. It has become central to understanding how modern economies function and evolve. Entrepreneurship research provides a framework for answering some of the most critical questions of our time. How are opportunities created and recognized? Why do some individuals pursue uncertainty while others avoid it? What drives innovation and economic transformation? These are not abstract curiosities. They are foundational issues that shape competitiveness, growth, and social progress.