News sufficiency: How generative AI summaries reduce news consumption in zero-click searches

Abstract

Generative artificial intelligence (GenAI) is rapidly reshaping the audience’s relationship with journalism, particularly through AI-generated summaries. Building on the observed patterns of limited visibility of sources, condensed summary presentation, and reduced contextual depth, we introduce the idea of news sufficiency, in which people encounter summarised content that feels enough to satisfy their immediate informational needs, thereby reducing the incentive to access full news articles. Empirically, this study examines differences between ChatGPT, Gemini, and Google Search when queried in European Portuguese, using three prompts: (a) asking for the main news of the day, (b) the latest on a specific news event, and (c) using only a basic keyword for that event. Drawing on a content analysis, we analysed 72 queries submitted by eight independent users. The results showed that platforms differ markedly in source attribution, summary structure, and contextual awareness. ChatGPT consistently provided hyperlinks and often clickable news images, while Gemini offered summaries only in text without citations. Both chatbots generated diverse and coherent news headlines capable of satisfying curiosity yet frequently failed to infer news intent from the basic keyword prompt, providing outdated or irrelevant information. The absence of Google’s AI Overview results during the observation window produced a contrast with a classic Google Search, which preserves user agency by requiring clicks on links. These findings have significant implications for journalistic authorship, editorial gatekeeping, and the economic sustainability of media, highlighting the need for AI literacy and platform governance that safeguards information pluralism.