Strategic resource mobilization for AI entrepreneurship in healthcare: Qualitative insights from startup founders

Abstract

Artificial intelligence (AI) has emerged as a critical focus for entrepreneurs, driving the development of AI-based startups to address challenges in various sectors, especially healthcare. Despite increased opportunities from greater data availability and supportive digitalization legislation, the healthcare industry remains resistant to disruptive technologies due to strict regulations. This resistance presents unique challenges for AI healthcare startups. Although literature investigates how startups handle the liability of newness and employ strategies such as using founder experience, participating in incubators, and forming alliances, little insight is provided into these challenges amidst the dual complexities of AI and healthcare. This study identifies the crucial elements for successfully launching AI healthcare startups amid multiple layers of complexity, including stringent regulations, data acquisition challenges, and advanced technology adoption. It conducts in-depth interviews with founders from 55 AI healthcare startups at various stages of development using a grounded theory approach. The findings highlight factors such as team structure, funding strategies, stakeholder engagement, and the role of data as a competitive asset. This research enriches the academic literature by deepening the understanding of success determinants in high-tech and regulated environments, challenging the jack-of-all-trades theory by underscoring the significance of diverse foundational team backgrounds, and refining the technology adoption framework by distinguishing between adoption patterns of physicians and patients. This research offers theoretical and practical contributions, aiming to foster improvements in patient care, efficiency, and overall healthcare outcomes through the innovations of AI startups.