How strategic decisions are formed and revised in an early-stage AI startup: A single case study of Weon

Abstract

Strategic decision-making under uncertainty poses a central challenge for early-stage startups, and this complexity is further amplified in AI-driven environments characterized by rapid technological advancements and unpredictable markets. This study examines how strategic decisions are shaped and revised in an early-stage AI startup, with a particular focus on the interplay between technological and market uncertainty, based on a qualitative single-case study. The findings show that strategic decision-making in an early-stage AI startup does not follow a linear or predetermined process, but is shaped as an iterative and emergent process, with direction gradually developed through experimentation, market interaction, and organizational learning. The process is characterized by recurring tensions between customer desires and the internal vision, between technical possibilities and market demands, and between short-term survival needs and long-term ambitions. In addition, contextual factors such as resource constraints and the rapid development of AI technology both limit and enable the strategic decisions that can be made and implemented. Based on these insights, the study contributes to the literature by developing a process-oriented understanding of strategic decision-making in early-stage AI startups, where technological and market uncertainty interact simultaneously and the tensions between these dimensions shape how strategic decision-making evolves over time.