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Every morning, Michelle Seo receives a briefing from Chattiana, her Muse artificial intelligence agent.
Seo is far from the first person to consume her news with an AI assist. In fact, the trend has become so common that some news outlets are starting to produce content that treats AI agents—not human readers—as the intended audience. This can look like anything from feeds optimized for AI to pieces structured to allow agents to create personalized articles.
“We believe that the media ecosystem is changing,” says Axios chief revenue officer Jacquelyn Cameron. “We see this with open web deteriorating. We see that search is shrinking. We see that hyperpersonalization is surging, that LLMs are becoming more important in the way that people are consuming” their news.
Major publishers have responded to that change in a variety of ways. Many, including WIRED’s parent company Condé Nast, have signed deals to allow AI platforms to surface their content. Outlets are grappling with “generative engine optimization,” or GEO, strategies to ensure articles appear in responses to AI prompts. Last year, AIOSEO, a SEO plug-in for WordPress sites, launched a feature that provides websites with LLM.txt files, which help AI discover and interpret sites’ content.
Others have taken a more defensive posture: The New York Times sued OpenAI and Microsoft in 2023 for copyright infringement, alleging that the companies illegally trained models on reporting. That case is still ongoing.
What Axios and a handful of others are trying, though, represents a more foundational shift in how the media operates—and who its stories are for.
“We have always said,” Cameron says, “that we want to be where the audience is.”
At the Digiday Publishing Summit in September, Axios announced the upcoming launch of Axios Direct: feeds designed for AI agents.
“We do believe that a significant portion of news consumption will move into AI systems, LLMs, and devices,” Cameron says. She describes the feeds as a more efficient way for agents to access Axios content, cutting back on narrative to prioritize structured data—more similar to a Bloomberg terminal than a series of articles.
Every’s founder Dan Shipper says the most common way Every’s content differs from a typical article is that its writers include prompts in pieces whenever possible, allowing readers to test concepts themselves. An article about a new model, for example, includes a series of prompts the reader can copy-paste into AI, demonstrating how the model answers questions and evaluates input.
Certain types of articles—such as guides—also include buttons that readers can press to “Read With Claude” or “Read With ChatGPT.” Clicking pulls up a prompt, instructing AI to “Start with a tight summary: one paragraph, bulleted. Then offer to go deeper.” Writers pack stories with details without worrying about losing readers’ attention, knowing agents will pick out the most relevant bits.
Two years ago, the outlet launched its first “extendable” article: a long-form feature accompanied by a database of reporting, from interview recordings to news articles to YouTube videos. Readers could query a chatbot, which would fetch additional details from the database.
“As a writer, you have to make choices about what goes into the story you’re telling,” Shipper says. “And there’s always a question about, are those the right choices? Or, are those the right choices for a particular reader?” With AI, journalists no longer choose.
“People are gonna do crazy, crazy stuff with this,” Shipper adds.
As outlets eye AI agents as a new audience, another question looms: Can publishers actually make money off of this?
Rasmus Kleis Nielsen, a professor of communication at the University of Copenhagen, says that while the market of publishing for agents is “emerging,” it remains immature and “extremely uneven.” Major questions remain, he says, about price points and how AI agents will interact with content in the future.
Cameron and Allison Murphy, Axios’ chief operating officer, are optimistic about AI as an audience proxy. According to the executives, Axios’s short-form, highly structured style has already made the publisher a favorite for AI to pull from, when responding to prompts. “Time is money for crawlers,” Murphy says. “They don’t want to have to go three quarters down the page to find the main point. So, that’s something that’s already benefiting us.”
But does AI crawling its content actually benefit Axios’ bottom line? Even if readers don’t actually visit the Axios homepage, the brand visibility in and of itself can be positive, Nielsen says. It’s not unlike publishers making content for social platforms like TikTok and Instagram that rarely bring viewers back to their websites.
Publications in general are grappling with how difficult it has become to monetize certain types of content when a chatbot can offer up answers on a silver platter. People only want to pay for information that other publications—and LLMs—don’t have. At Every, that means in-the-weeds guidance on AI and how to use it; at Axios Pro Deals, it’s speedy access to information that could move the market. An all-access Axios Pro Deals subscription costs $2,499 a year, while an annual Every subscription costs $288.
Shipper sees that $288 as a subscription for a human reader, along with their agents. “I may not want to read all of your stuff every month,” Shipper says. But if his subscription can include his agent, “I may want my agent to know it so that it can tell me, ‘Hey, this thing is important.’”
Murphy says that Axios’ starting point is one of acceptance: People are already using AI to absorb information, and that more people will be doing so in the near future.
“I also try to make it a little less existentially terrifying by thinking, this isn’t the first time this has happened in media,” Murphy says. People get their news via social media, via short-form video, via podcasts. “It isn’t really AI as the audience,” Murphy adds. “It’s AI as a tool that helps us reach our audience.”