Generative AI in Management Research: Assistant, Co-Author, or Contaminant?
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Abstract
Generative artificial intelligence has moved from the margins to the center of management research in the space of three years, yet the scholarly community still lacks a shared vocabulary for distinguishing legitimate from illegitimate uses across the research lifecycle. This editorial argues that the technology is neither an assistant to be celebrated uncritically, a co-author to be credited, nor a contaminant to be banned; it is a general-purpose instrument whose legitimacy depends on where it is used, how its outputs are verified, and whether its role is disclosed. We propose a reflexive checklist of five dimensions for deciding whether to use AI at a given stage of research, map seven levels of AI involvement from language polishing to autonomous research agents, and introduce a decision framework organized by the verifiability of AI outputs and their centrality to the scholarly contribution. The editorial concludes with the Brazilian Administration Review’s explicit expectations for AI-assisted submissions, including a structured disclosure policy, full author accountability, symmetric obligations for reviewers, and a commitment not to use AI-detection software in editorial decisions. Transparency, not prohibition, is the standard the field needs.
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