Generative artificial intelligence (AI) has rapidly become embedded in academic writing, assisting with tasks ranging from language editing to drafting text and producing evidence. Despite the wide range of AI use, the expectations for disclosure remain inconsistent. Several journals use binary disclosure statements that fail to distinguish minor language assistance from uses that have a significant impact on the manuscript structure and data interpretation. This article proposes a risk-proportional approach separating disclosure by risk.

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