Abstract The rapid diffusion of generative artificial intelligence (GenAI) has triggered a transformative shift in how organizations approach decision-making. Despite growing enthusiasm and widespread adoption across industries, GenAI’s specific tasks and roles, and the ways in which they shape the interplay of human cognition and algorithmic enhancement in organizational decision-making, remain insufficiently understood. Addressing this gap, this study conducts a systematic literature review that identifies 68 relevant publications to synthesize and advance current knowledge on the integration of GenAI into decision-making. The study identifies 53 tasks performed by generative applications, aggregates them into 18 task categories, and maps these tasks and categories onto six recursive decision-making components: attention, intelligence, design, choice, implementation, and feedback. Building on the harmonization and translation of these tasks, we propose a typology comprising six active GenAI roles and one collaborative human-AI role. We then develop a processual framework that specifies how and when GenAI is embedded within organizational decision-making processes, delineating how generative applications support, augment, or co-perform decision-making activities. Our findings reveal a fragmented application landscape and highlight the limited integration of GenAI in the choice phase of organizational decision-making. By offering a structured typology and a processual conceptual framework, this study clarifies the evolving interplay between human decision-makers and generative technologies. In doing so, it provides a foundation for theory-advancing research and for more explicit and actionable managerial practice.
Schulte et al. (Tue,) studied this question.
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