Augmented or Undermined? The Positive and Negative Effects of Generative AI on Product Management: A Rapid Structured Review

Generative artificial intelligence is increasingly entering product-management work through research synthesis, ideation, requirements drafting, artifact evaluation, analytics, and stakeholder communication. This rapid structured review examines when GenAI augments product judgment and when it undermines it. Eighteen candidate publications were screened through 2 September 2026, of which sixteen were retained: three direct product-management empirical studies, six product and innovation contextual sources, and seven adjacent empirical studies from knowledge work and software development. The evidence identifies benefits including faster completion of bounded tasks, repeatable critique, idea expansion, improved knowledge access, and support for less-experienced workers. Reported risks include inaccurate outputs, overreliance, homogenization, reduced critical-thinking effort, skill erosion, weakened peer interaction, privacy concerns, and diffused accountability. The paper proposes an AI–PM Dual-Impact Framework based on task–model fit, grounding, expertise, verification, human ownership, and organizational support. The findings support selective, governed adoption rather than universal automation. This manuscript is a preprint and has not undergone peer review. The supporting screening and evidence-extraction tracker accompanies the paper.