This Special Issue brings together twelve original articles that examine, from diverse disciplinary and geographic vantage points, how the media shapes narratives about technological innovation and how AI specifically is influencing media practice, public understanding, and social life more broadly. The contributions span computational communication research, journalism studies, media education, environmental communication, political economy, and cultural studies. They draw on studies conducted in Europe, Africa, the Middle East, and across digital platforms that transcend national borders. The result is a comparative and multi-perspectival collection that resists both the techno-optimism that frequently characterises industry commentary and the undifferentiated techno-pessimism that sometimes characterises critical scholarship.

Abstract. This study investigated the impact of AI-driven automated publishing services (APSs) on the editorial character of news content disseminated via Facebook. While previous research suggests that human editors adapt news to social media logic, which often results in news softening, the specific influence of APSs on this process remains unexplored. As German newsrooms increasingly implement APSs, editorial decisions are partially transferred to algorithms that select, adapt, and publish news based on publishers’ content feeds. This automation raises concerns about potential erosion of journalistic standards and the systematic alteration of news content on social media platforms. Our analysis encompasses 2.6 million Facebook posts from 44 German news outlets; the posts were published between 2018 and 2023. We found that, in 2023, 57% of these outlets used APSs; however, they primarily used a semi-automated approach that allows manual oversight of topic selection and stylistic adaptation.

Abstract. This article presents the first comprehensive study of Artificial Intelligence (AI) integration within the Portuguese news media landscape, based on a mixed-methods design combining a systematic literature review, a nationwide survey, and focus groups. The findings reveal a two-tiered ecosystem: while large multimedia conglomerates based in urban centres are beginning to institutionalise AI for tasks such as data processing and content distribution, adoption in regional and local newsrooms remains fragmented, driven largely by individual initiative. Journalists primarily deploy AI for routine, often invisible tasks – including transcription, translation, and search engine optimisation – while expressing ethical reservations about the use of AI in automated content production. Key professional concerns include the “efficiency paradox,” the implications of synthetic media for disinformation, and the potential erosion of journalistic authorship.

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.

The conversation in marketing right now is about how to optimize for AI-powered discovery: Generative Engine. Optimization (GEO), Answer Engine Optimization (AEO), prompt engineering, and structured data for agents. But optimization without measurement is guesswork. A brand cannot know whether its GEO investment is working, whether its share of voice in AI responses is growing or shrinking, or whether a competitor is gaining ground unless there is a common standard for measuring any of it.

Why raw content ownership is no longer enough, and how smart publishers are turning proprietary data into high-value operational dependencies.

The AI Information Map is a research project of the Media and Journalism Research Center (MJRC) that investigates how artificial intelligence systems present news, public affairs and media sources to users. As millions of people begin to use AI assistants, answer engines and search-integrated chatbots to ask about politics, current affairs, media ownership and public institutions, AI systems are becoming new intermediaries between citizens and the news. These systems do not browse the news like humans do. They select, summarise, rank, recommend and sometimes omit sources before users ever reach the original journalism.

With human oversight increasingly under pressure, 20 media managers explain how they are reshaping their workflows and outputs in light of the rise of AI