Peer Review 2027: Scenarios for Academic Publishing in the Age of AI

The practices of peer review and the broader landscape of academic publishing are under strain. Submission rates are rising, placing greater demands on editorial and reviewer capacity. The use of LLMs in the production of academic papers threatens to accelerate these trends beyond the breaking point. This article is the product of a meeting of editors of academic journals across political science, sociology, and communication science to discuss the issue of LLMs in academic publishing. We argue that peer review is an essential and irreplaceably human component of social science: if elements of the research process traditionally done by humans are substituted by AI, humans should increase their involvement with the evaluation of research. We present a scenario-casting exercise illustrating four possible equilibria for the incorporation of LLMs into the publication ecosystem, and we discuss the various levers that academic journals have at their disposal to navigate the changing landscape. We emphasize that adaptive policies with built-in evaluation mechanisms, feedback loops, and a capacity for revision are required, along with new streams of metascientific data to remain up to date as AI and its adoption continue to evolve.