For 16 years now, we've asked smart people what they think will happen in the coming year in the world of journalism and digital media. And this year's collection of predictions, published last month, is the biggest - and, I think, the best - yet. (I may be uniquely qualified to make that judgment, as I am certainly the only human to have read all 1,881 predictions we've ever published.)
For all the anxiety over how AI will upend journalism as we know it, I continue to believe its best immediate uses in our profession remain exceedingly mundane. Among them, extracting structured data from unstructured text: identifying people, places, and events buried in articles; applying metadata and complex taxonomies that reporters and editors don't have the patience to maintain; normalizing things like locations, spellings, names, and entities so they line up cleanly with external databases.
As AI accelerates and expands in media, journalism needs a pedagogy of wonder. This is an approach in education that encourages students to be critical, curious, and creative. For journalists, a pedagogy of wonder calls on them to become explorers, treating AI as a partner in inquiry to help them ask better questions, notice more, and deepen public understanding. It treats the newsroom as a learning space where curiosity is a method, and ethics is a practice.
Audiences increasingly evaluate individual pieces of information and contributors rather than trusting institutional brands wholesale. They assemble their understanding of the world as a patchwork: a podcast recap, a TikTok debunk, a Reddit thread, a traditional news article. Pew finds that about one in five U.S. adults now regularly get news from influencers on social platforms, often citing helping them to understand the issues and perceived authenticity. The numbers are higher for younger generations.
In fact, a recent report on the use of AI in news media from the Reuters Institute showed a pretty clear pattern of audiences' trust declining the more AI was used in the journalistic process. Only 12% of people were comfortable with fully AI-generated content, increasing to 21% for mostly AI, 43% for mostly human, and a respectable (but, notably, not amazing) 62% for fully human content.
The question today isn't whether we are using AI in journalism, because we do it already," but whether "we can do journalism without outsourcing our skepticism, our ethics, and our sense of accountability, both as journalists ourselves and the accountability we are asking people and organizations that hold power to provide," said Sideris who is studying how generative AI can better assist investigative reporting as a 2026 Nieman Fellow.
The Connecticut Mirror's new artificial intelligence data reporter and product developer is trying to figure out how to tell stories that were previously impossible because of the volume of documents or deadline pressure. In Connecticut, where news is often made in municipal meetings, the nonprofit's beat reporters can't make it to all 169 different towns, Eichhorst said. One of her goals is to generate leads and get material from those meetings to reporters using AI tools.
