“AI adoption in early-stage FinTech startups influencing the traditional decision-making process under conditions of uncertainty.” - Lauret,Stan; Elsner,Tammo (2025)
This thesis investigates how early-stage FinTech startups integrate Artificial Intelligence (AI) into strategic decision-making processes under conditions of uncertainty. By employing the OODA loop (Observe, Orient, Decide, Act) as a foundational framework, the study examines the evolving role of AI within each phase of the decision-making cycle. Drawing on nine in-depth interviews with founders and decision-makers across European FinTech ventures, the findings reveal a nuanced pattern of AI usage: from operational assistance in the "Observe" and "Act" stages, to interpretive support in "Orient," and human-AI collaboration in "Decide." Notably, the study identifies a critical gap in existing frameworks by highlighting the absence of a monitoring or post-action feedback phase. To address this, a revised OODA model is proposed, integrating a fifth phase centered on monitoring. The results underscore AI's augmentative value rather than a purely automating force. This research contributes both theoretically and practically by refining decision-making models and offering actionable insights for AI adoption strategies in modern entrepreneurial settings.
Keywords: Entrepreneurship; FinTech; Decision-Making; OODA Loop; AI Adoption; Uncertainty