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Liquid content gives publishers more ways to package, distribute, personalize, and monetize journalism as audience habits shift. #
AI is prompting the deconstruction of the traditional news article. Publishers concerned about declining search visibility must adapt their content distribution workflows to surface in Google’s AI-powered SERP features and LLMs.
AI-powered algorithms are reshaping how news content gets surfaced, with audiences favoring video in a social-search hybrid experience. The article isn’t dead, but publishers may need to think beyond it and embrace liquid content.
Nikita Roy captured this shift during her presentation at ONA25:
- “The article is no longer the unit of journalism in an AI-mediated world.”
Roy also challenged the audience:
- “If you knew nothing about newsrooms, only that people need trusted, verified information, what would you build with today’s tech?”
What is liquid content? #
There’s no consensus yet on what “liquid content” means, much like the GEO/AEO/AI SEO debate. I like the definition shared in the Reuters Institute’s 2026 trends and predictions report:
- “[Liquid content] describes content or stories that are not static but adapt in real time based on the viewer’s context, location, time, or interaction. AI facilitates this by tailoring content to individual preferences. Requires traditional media companies to move away from authoring ‘articles’ towards more flexible atomic objects.”
Traditional article components are all still present and valuable:
- Verified information.
- Quotes.
- Data.
- Resources.
Instead of locking them in a rigid article container, the components are plugged into flexible content delivery pipelines. The value shifts from the article as a whole to the facts and figures within it.
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How multimodal content fits into liquid content #
Multimodal content and liquid content are sometimes used interchangeably. It may be more useful to think of multimodal content as what flows through a liquid content distribution system, powered by two critical components:
- Format.
- Personalization.
The key is to align a publisher’s topical strengths with the format preferences of its audience.
A well-known multimodal content generator is Google’s Gemini Notebook (formerly known as NotebookLM). Give it a PDF of a court ruling, a video explainer, or a 2,000-word deep-dive investigative report, and it can convert the information into a variety of other formats: briefings, infographics, quizzes, podcasts, and slide decks.
I’ve had mixed experiences converting data analysis reports into accurate infographics, but that’s expected with AI technology. It’s still a worthwhile tool for testing multimodal options. Here’s the infographic NotebookLM generated for this article.
Dig deeper: Utility news content: How to win beyond clicks in AI search
Adapting newsroom workflows for liquid content #
To build liquid content workflows, a newsroom’s CMS must have the capability to convert an article into different formats. This shouldn’t be a fully machine-based process, however. Human input is essential.
Instead of forcing a story to fit a default article format, the story is allowed to dictate how it’s presented in a way that will best resonate with its intended audience. Steven Wilson-Beales recommends asking:
- “What is the essential seed of the story and what are the best formats that will allow that seed to bloom?”
Reformatting content is not a new practice, and publishers are already well-versed in headline A/B testing. With AI, they can test formats in a similar way to discover what resonates best with their audiences.
The more challenging part is the personalization layer.
Finnish broadcaster Yle has been working on personalization efforts for over a decade. AI technology can now help bring some of its concepts to fruition, such as serving up story formats tailored to a user’s current need (an audio version for a driver vs. a text-based article for a subway rider).
Publishers are already experimenting with multimodal and liquid content in different ways:
Sky News: Revamping workflows to simultaneously develop projects across multiple distribution platforms instead of converting to digital after television broadcast.Die Zeit: Focusing on podcasts as a multiformat opportunity.AP’s Storytelling tool: Adapts stories into a variety of formats, from social posts to push alerts.The Washington Post: Launched an AI experiment in late 2025 with a customizable “Your Personal Podcast” in which the audience can choose its preference of topics and hosts. Its bumpy rollout shouldn’t be an excuse for publishers to avoid AI-powered experiments in their newsrooms, as these pioneering projects can offer valuable takeaways to build better-quality products in the future.
Structuring articles for AI search #
Liquid content is all about flexibility, but it still needs to be structured so that Google’s AI search features and LLMs can easily surface and cite it.
This means being aware of how AI bots process and extract content, but not writing solely for them. Instead, what’s good for bots can be good for a publisher’s audience.
Elements to consider:
- Don’t bury the lede. Instead, apply the inverted pyramid structure.
- Use
structured data.NewsArticle - Include bullet-point summaries at the top of articles, especially for long pieces.
- Add subheaders to organize and define sections.
- Identify the key questions, lessons, or quotes from the article and highlight them in a quote box or similar artifact.
- Leverage internal linking to deepen audience engagement and broadcast topic authority.
The last thing news publishers should do is pivot from writing for search algorithms to writing for AI algorithms. Smart article structure and formatting can help news content reach both bots and busy human readers.
While it may seem like news attention is shrinking, it may be more about matching audiences with their preferred platform and format. In a world plagued by news fatigue, liquid content products could be a transformative experience for news consumers. Dig deeper: How to optimize news content for today’s social-first Google SERP
New ways to distribute and monetize news content #
Liquid content offers the media industry an opportunity to transition from leasing space on third-party platforms to owning content pipes filled with valuable, exclusive data. It’s a pivot that requires clear-eyed purpose, focus, and experimentation to become profitable.
I like to use a restaurant as a model for what a thriving liquid content model could look like in a newsroom. A restaurant offers a menu of standard dishes but adapts according to its patrons’ dietary, budget, and atmosphere preferences.
Similarly, a publisher’s content offerings (website, newsletter, app) serve as its menu. By adopting a liquid content workflow, publishers move from a fixed menu to a dynamic à la carte experience tailored to audience preferences.
Monetizing publisher data
A 2025 FT Strategies report proposed “journalism as a service” (JaaS), where publishers could monetize exclusive data via APIs or licensing.
Financial news publishers may have the current edge here, but health, science, and sports publishers are sitting on a treasure trove of historic data insights.
Local publications have similar opportunities to become AI-powered community resource centers or, as Splice Media calls the concept, “Nextdoor for machines.”
Opportunities for affiliate content
Publishers shouldn’t overlook affiliate content. AI shopping features added to the SERPs, paired with updates to Google’s site reputation abuse policy, have left some publishers reeling, while others seek new opportunities.
Time is working on a data product designed exclusively for bots, recognizing the growing potential in agentic AI, where bots make purchases on behalf of users.
Can publishers regain their affiliate content footing by becoming a shopping bot’s trusted product review source?
Finding the right distribution platforms
Liquid content can be directed to flow to platforms with the best engagement opportunities. For example, sports viewership is growing on social media, with fans watching highlight clips and creator content instead of watching entire games on broadcast TV.
Publishers must dig into their analytics tools to understand not only their social performance but also how their social posts show up in search. Google is making it easier to track by adding a publisher’s social and video platform data to Search Console.
Personalizing content distribution
Google is also pushing personalization in its AI-powered news search features. Preferred Sources is designed to help dedicated consumers connect with their favorite news publishers and subscriptions.
Barry Adams says Google’s personalization features amount to building an audience loyalty ecosystem. Content that engages a dedicated news brand follower, such as in-depth explainers, becomes a lead magnet for a publisher’s other profitable products, including newsletters, subscriptions, and apps.
Other promising developments include Nota, which uses AI to help monetize publisher content as audience interest spikes. Beakon is an AI-powered reader personalization service for financial news. I expect this corner of the industry to expand rapidly in the coming years.
Dig deeper: Content alone isn’t enough: Why SEO now requires distribution
The risks of liquid content #
Most newsrooms (64%) still develop stories based on the channel destination (website, print, TV) rather than audience preference (21%), the Future Newsrooms Study 2026 found. Publishers may feel like they are out of pivots, but risk being left behind by publisher brands that are more open to experimentation.
When articles are reduced to informational atoms, the loss of meaning is a real risk. We’ve all seen AI Overviews generate misinformation based on slicing and dicing multiple sources into a Franken-answer.
I’ve documented Google’s AI rewriting headlines on Discover, providing fictional scores for a game that hadn’t even started yet. Publishers may own what flows into the pipes, but Google is at the controls of its Freestyle SERP machine, generating an AI slop concoction with a publisher brand stamped on it.
Focusing on news content personalization may strengthen the echo chambers that much of society has willingly embraced over the last decade. By giving people wider control over their news consumption experience, they may choose to narrow their perspective to one that suits their worldview.
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Making liquid content work for publishers #
AI search is prompting a transformation of the traditional article format in which articles become repositories of flexible data assets that power AI search responses and LLM citations.
Publishers should optimize the valuable data they own to ensure they can monetize their products in a liquid content workflow. If implemented strategically, this pivot could create much-needed new revenue opportunities for the media industry.
Dig deeper: Hidden gem publishers outperform major media on audience affinity: Study
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