Mapping the early-stage AI startup success: A grounded theory approach to technology entrepreneurship leadership

Abstract

This research investigates the foundational leadership attributes that drive the success of early-stage technology startups, particularly within the artificial intelligence (A.I.) sector, and their capacity to secure venture capital. Employing the grounded theory approach, this study analyzes data from over three decades of speeches, interviews, and presentations by prominent venture capitalists and technology entrepreneurs. The analysis identifies a comprehensive leadership model encompassing both Endogenous Entrepreneurship Leadership-attributes and competencies cultivated through education and experience-and Exogenous Entrepreneurship Leadership-qualities linked to market dynamics and industry-specific acumen. Furthermore, the study introduces a novel perspective on entrepreneurship education, advocating for integrating these identified leadership elements into educational curricula from an early stage. This research enriches the theoretical discourse on technology entrepreneurship leadership and offers actionable insights for enhancing entrepreneurship education in the evolving landscape of AI-driven innovation.