This is an excerpt from our Digiday+ Research report “How publishers from Dow Jones and Business Insider to People Inc. are approaching AI in 2026,” which explores how publishers are navigating the opportunities and challenges that have come with the evolution of AI. The report is based on a survey of 40 publisher professionals, as well as individual interviews with publisher executives responsible for AI investments and applications development.
AI has moved from the margins to the mainstream of editorial workflows. Publishers have increasingly embedded AI tools into daily functions, especially when it comes to streamlining tasks and improving the audience experience.
This is according to a Digiday+ Research survey conducted in the fourth quarter of 2025.
When Digiday asked publishers which applications their companies are using AI for, three applications tied for the No. 1 spot. Fifty-three percent of publisher respondents said their companies use AI for internal chatbots and AI assistants, voice-to-text translation, and multi-media generation, respectively. This tracks with Digiday’s survey finding that more than half of publishers use AI for internal purposes.
When publishers use AI for internal purposes, it’s usually to automate tasks that would take humans longer to complete. Voice-to-text translation and multi-media generation, including images, videos and music, are two tasks for which publishers use AI to save time.
The most common example of voice-to-text translation is using an AI application to transcribe an interview. However, voice-to-text translation can also be used for translating articles from one language into another. Dow Jones developed an AI-assisted auto-translation service that uses an LLM model to translate English-language news content into Korean and other languages, increasing the publication’s audience reach.
“We expanded to Japanese, German, French and Arabic, and the process has been refined,” said Ingrid Verschuren, evp of data and AI and general manager of EMEA at Dow Jones. “Ultimately it opened up a new market for us. If you use human translation, there’s always going to be a lag between when the English version publishes and when the other version publishes. … By using AI translation, we reduce lag much further than if it was human translation.”
Similarly, The New York Times offers a “listen to this article” feature through which readers can select to have an AI-generated voice read articles to them.
AI-backed multi-media generation also has a wide range of publisher uses. Commonly, publishers use AI to create images for audience-facing content. However, many publishers are also using AI-backed applications to edit video or audio content.
In 2025, Reuters experimented with using an AI agent to increase the speed of its video production process by asking AI to produce a rough edit of videos so that humans could focus on refining the final cut.
“We’ve asked the LLM to pick the best bits and create what we call a wrap edit. And it’s actually doing quite a good job,” Rob Lang, newsroom AI editor at Reuters, said at the Digiday Publishing Summit in October 2025. “That’s without even having that multimodal. So, if we can actually get the AI as an agentic AI system to understand that, to be able to look at things and compile things, we might be able to get the AI to build the edits for us, which would be quite extraordinary.”
Publishers are also using AI for internal purposes beyond multi-media generation and text-to-voice translation, such as data analysis, content creation and content management.
The New York Times uses AI to parse video and data points for its investigative reporting. In 2024, the editorial team used AI tools to sort through 500 hours of leaked Zoom recordings from an election interference group ahead of Election Day.
“You can’t Google 10,000 names … but a computer can Google 10,000 names,” said Zach Seward, editorial director of AI initiatives at The New York Times. “And then using AI, we could analyze those search results for certain markers that [the reporter] was interested in.”
Dow Jones’ Verschuren said the publisher has been using AI in some capacity for years — from adding descriptive keywords or categories to news articles, to analyzing data. “I was hired to manually tag news articles more than 25 years ago. … Three years later, that was completely automated,” Verschuren said.
“The biggest impact is where the machine does a better job,” she added. “The newsroom did a large investigation about airplane fumes involving analysis of over a million aviation reports. We used a combination of traditional machine learning on top of LLMs. It would have been impossible to do manually. … In the newsroom especially, the opportunity to analyze large data sets allows reporters to move faster and spend more time on editorial judgments.”
Harry Hope, CTO at Business Insider, said the publisher has integrated AI tools into its CMS to expedite the publishing process. “Not writing the article, but generating metadata and behind-the-scenes things like titles for social platforms, category tags and taxonomy terms that we want to associate with a given story,” Hope said. “Those are intended to decrease production time and increase the velocity at which we publish. It allows writers and editors a chance to focus on the story itself, and not the nuts and bolts of publishing in a digital environment.”
“We’ve found that AI is better at doing that than humans, and humans would much rather focus on the story itself,” Hope added. “That’s where the real value is for our readers at the end of the day.”
According to Digiday’s survey, 37% of respondents said their companies use AI for content recommendation, 33% said they use AI for copy generation and 30% said they use the tech for advanced search.
Some publishers are using AI copy generation for marketing purposes like creating ads or social media posts, while others use AI for internal editorial tasks like writing article summaries — all with human oversight.
Business Insider uses AI to provide readers with content recommendations and to power search, a feature the publisher launched in June 2025. “We’ve been using various permutations of a content recommendation or personalization algorithm for quite a while,” Hope said. “We’ve also rolled out a more sophisticated feature that we call the AI audio briefing — our attempt to take everything we learned from search and roll it out in a way that was ideally more useful for members that don’t want to search, or want a more passive experience.”
Forbes is also using AI applications to improve content recommendations, according to Nina Gould, the publisher’s chief innovation officer. “We’re starting to use generative AI more in content recommendations and how we can get better contextual recommendations for folks — based on not just the story they’re reading, but on anything that we know about their journey to that story, preferences they’ve told us or that we’ve observed,” she said.
“We’ve seen material lifts in click-through rates,” Gould added. “That’s hugely impactful in a zero-click search world. When you have less people coming into your site, you need to focus on not just getting them, but how you can demonstrate value to build loyalty and get them to come back. Having good content recommendations and demonstrating the depth of our content is really helpful.”
For more, read the full report.
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