The first time I heard the phrase “liquid content” was in 2024 at INMA’s Media Innovation Week in Helsinki. Executives at Yle described something that felt immediately familiar yet difficult to name: the sense that journalism was starting to move beyond fixed formats.

News was no longer just an article, a video, or a podcast. It was something more fluid, something that could move between formats depending on how audiences wanted to consume it. 

What is liquid content?

As Mika Rahkonen, head of strategy at Yle, succinctly explained it: “We’re in an era of liquid content where we watch audio, we listen to text, and read video.”

At the time, it felt slightly abstract. An interesting way of describing the growing overlap between media formats. But over the past year, that idea has only become clearer.

Nic Newman recently offered a more structured definition in the Reuters Institute Journalism, media and technology trends and predictions 2026: “Content that adapts in real time to the user’s context, location, or interaction — enabled by AI and built from flexible, reusable content blocks.”

Liquid content is not just about formats blending together. It is about journalism becoming modular, dynamic, and responsive. AI is the infrastructure that makes this possible.

For most of the digital era, publishers have thought about content in terms of finished products. A story is written. A video is edited. A podcast episode is produced. Each format is created separately, even if they originate from the same reporting.

Liquid content challenges that entire model.

Instead of producing individual pieces for each channel, the starting point becomes structured knowledge — facts, quotes, context, analysis — that can flow across formats. The same underlying reporting can become a written article, an audio briefing, a conversational answer, or a short video explanation, without much human intervention. 

In other words, the story becomes the source of truth, and formats become expressions of it.

How AI fits in

This is where AI begins to play a critical role.

AI systems can transform, adapt, summarise, and translate content across formats in real time. They can generate audio from text, extract key facts for conversational answers, or turn reporting into short explainers tailored to different audiences.

What once required multiple production workflows can now emerge from a single structured foundation.

Nic Newman’s definition highlights another key dimension: context. Liquid content isn’t just about format flexibility. It’s also about responsiveness.

Imagine journalism that changes depending on:

• Where the user is.

• What device they’re using.

• How much time they have.

• What they already know about a topic.

A commuter might receive a short audio briefing. A reader at home might explore a full analysis. An AI assistant might extract a single verified fact from the same reporting. In fact, the same piece of content may never be shown more than once.  

The underlying journalism remains the same, but its presentation adapts. This is a fundamentally different way of thinking about publishing.

How infrastructure fits in

For many publishers, the biggest obstacle is not imagination — it is infrastructure. Most newsroom systems were designed for static outputs: articles, galleries, videos. They struggle to treat journalism as structured data that can flow between systems.

But if content is going to become liquid, the architecture behind it must change too. That means:

• Structuring journalism into reusable components. 

• Separating facts, analysis, and context.

• Making content machine-readable.

• Designing workflows where formats are generated dynamically.

Another way to look at it: Liquid content requires liquid infrastructure.

The reason the idea of liquid content feels so relevant today is the interfaces to information are changing. Search is shifting toward answers. AI assistants are becoming information gateways. Audio, video, and text are increasingly interchangeable. And in this environment, rigid formats become a limitation.

But journalism built as flexible, structured knowledge can move freely across these new interfaces, retaining attribution, context, and trust along the way.

And that might be the most important takeaway of all: Liquid content isn’t about abandoning journalism’s foundations. It’s about building systems where journalism can flow wherever audiences — and increasingly AI agents — need it to go. 

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