InsightForge: Deriving Entrepreneurial Insights from Open-Ended and Unstructured Survey Data Using NLP Techniques

Entrepreneurship has long been recognized as a key driver of economic development, traditionally centered on business creation and the strategic actions of individuals aiming to realize their entrepreneurial visions. Central to this process has been the business plan, often viewed as a critical blueprint that outlines the vision, strategies, and operations of new ventures. However, recent studies and observations have raised concerns regarding the continued relevance of business plans, suggesting a shift in entrepreneurial behavior. In response, this study adopts a novel approach by using artificial intelligence (AI) to explore entrepreneurial practices more rigorously. Written feedback from 150 entrepreneurs was analyzed using natural language processing (NLP) techniques, allowing us to move beyond subjective assessments and anecdotal evidence. Our study utilized a structured twenty-question survey to capture the experiences and insights of entrepreneurs. By applying AI, we were able to process large amounts of textual data, uncover nuanced patterns, and identify correlations that might otherwise go unnoticed. The proposed approach enabled a comprehensive analysis of entrepreneurial decision making and provided a robust framework for future research. The findings from this work offer valuable insights into the evolving landscape of entrepreneurship, with significant implications for education, policy, and practice in today’s dynamic business environment.