Abstract
Artificial intelligence (AI), particularly generative AI, is widely expected to transform organizations, yet effective adoption and use remain challenging. Although organizations recognize AI’s potential, capability gaps and unintended employee-level consequences persist. Despite rapid growth, management research on AI in organizations is fragmented across domains, levels of analysis, and assumptions. This article presents a systematic literature review of 458 peer-reviewed business and management studies published between 1991 and 2025. Adopting a longitudinal and integrative perspective, we expose implicit assumptions about AI, clarify core constructs by distinguishing analytically distinct domains (e.g. development, adoption, use, and impact), and establish field-level boundary conditions. The review reveals a heterogeneous and unevenly developed research landscape and offers a framework and methodological approach to guide cumulative and coherent future research.