AI와 인간의 상호작용: 전략경영 관점에서 본 연구 동향과 전망

This study provides a systematic review of research on human–AI interaction and its implications for individuals’ task performance and decision-making, and outlines directions for future research. To this end, we analyze 40 studies focusing on individual-level phenomena, drawn from top-tier academic journals listed in the Financial Times 50 as well as recent high-impact working papers. We examine human–AI interaction through four perspectives—substitution, complementarity, learning from AI, and AI as an autonomous agent—and argue that AI is not merely a substitute for human labor. Rather, it frequently functions as a complementary resource that enhances individual capabilities. Importantly, the effects of AI are highly heterogeneous: they vary across individuals and situational contexts and evolve dynamically over the course of human–AI interaction. These findings suggest that analyses of human–AI interaction should account for granular task-level variation, temporal dynamics, and resulting heterogeneity in outcomes. Building on this review, we argue that future strategic management research on AI should consider the technology’s rapid evolution and its increasing integration with other technologies, such as robotics. At the same time, such research must address key challenges, including the availability of reliable data for causal inference and the management of ethical concerns, in order to advance a broader and more rigorous set of research questions and methodological approaches.