Since ChatGPT burst into public view in late 2022, artificial intelligence has moved in a very short time from being an exploratory technology to becoming an everyday component of journalistic work. In that accelerated transition, the initial conversation — dominated by surprise, enthusiasm, and also fear — has given way to a deeper, less technological question: what role does artificial intelligence actually play in the journalistic profession and in the daily life of newsrooms.
Unlike previous transformations, the impact of AI is not limited to a new distribution channel or a specific tool. Its incorporation puts pressure on editorial processes, redefines professional roles, modifies production routines, and forces a review of longstanding criteria on authorship, responsibility, verification, and the value of journalistic work. It is not just a matter of doing faster what was already done, but of revisiting how, for what purpose, and under what principles information is produced in an ecosystem shaped by automated systems.
Placing this transformation in historical perspective allows us to gauge its depth. The emergence of the printing press in the fifteenth century, radio, television, the mass adoption of the internet, Web 2.0, and mobile phones in the twenty-first century can be cited as inflection points that marked a before and after in our relationship with media, technology, and information. As happened with each of those technologies, artificial intelligence is inscribed in that long sequence of changes that altered the relationship between media, audiences, and power. There is, however, a key difference: this time the technology not only mediates the distribution of content, but intervenes directly in the cognitive processes that historically belonged exclusively to human work — such as writing, summarizing, classifying, prioritizing, or suggesting narrative angles.
Artificial intelligence offers concrete opportunities for journalism: it makes it possible to automate repetitive tasks, expand analytical capabilities, accelerate workflows, explore new formats, and establish new relationships with audiences. This frees up time for journalists and editors to focus on creative aspects and higher-value analytical processes, such as producing high-quality content and interpreting complex data. Used appropriately and purposefully, generative AI can function as a tool that amplifies the cognitive abilities and processing capacity of those who practice journalism — expanding their creative frontiers, improving efficiency in newsrooms, increasing content relevance, and generating a direct impact on the sustainability of media organizations.
Yet those opportunities only materialize when clear criteria, editorial oversight, ongoing training, and explicit usage frameworks exist. Without them, adoption becomes fragmented, informal, and dependent on individual initiatives — reproducing old problems beneath a layer of technological innovation. Accumulated experience in newsrooms of different sizes and regions shows that the main obstacles to sustainable adoption are not technical, but cultural, organizational, and strategic. The rapid advance of AI also renews debates around topics such as data privacy and security, disinformation, algorithmic bias, and the access gap that generates inequality between regions.
In this context, the debate about artificial intelligence in journalism cannot be reduced to a list of tools or a promise of efficiency. The availability of generative platforms coexists with newsrooms shaped by resource asymmetries, gaps in knowledge, production pressures, and business models under strain. The growing integration of this technology into newsrooms is marking an era in the recent history of media, transforming a significant share of the productive processes established up to today.
This guide starts from a central premise: artificial intelligence does not transform newsrooms on its own. It is people, processes, and editorial decisions that determine its real impact. For this reason, rather than explaining how AI systems work, this work aims to offer a structural perspective on how to integrate them consciously, gradually, and responsibly in diverse journalistic organizations.
From the Redacciones5G program, this transformation has been closely accompanied through the creation and development of training programs, consulting, analysis of real cases applied in media organizations, experimentation with generative tools, publication of articles, interviews, and an open, ongoing dialogue with journalists, editors, and media executives across the Ibero-American region. That journey made it possible to identify recurring patterns, common tensions, and shared learnings that go beyond the specific context of each newsroom.
Based on those experiences, this new edition of PeriodismoIA presents itself as an editorial roadmap to help journalists and media managers think about artificial intelligence not as a passing novelty, but as infrastructure that is already reconfiguring journalism. A guide for making informed decisions, designing one's own usage frameworks, and ensuring that technological adoption moves at the pace of the professional reflection that must accompany it.