Publishers Adapt Content for AI Search and Liquid Formats

News publishers face a critical need to adapt their content distribution workflows to ensure visibility within Google's AI-powered Search Engine Results Pages (SERPs) and Large Language Models (LLMs), as AI algorithms fundamentally reshape how news content is surfaced. This shift is occurring alongside a growing audience preference for video and a hybrid social-search experience. The traditional news article, while not obsolete, is being re-evaluated as the primary unit of journalism in an AI-mediated information landscape. Nikita Roy highlighted this evolution at ONA25, stating, "The article is no longer the unit of journalism in an AI-mediated world." Roy also posed a thought-provoking question to industry professionals: "If you knew nothing about newsrooms, only that people need trusted, verified information, what would you build with today’s tech?"

The concept of "liquid content" is emerging as a response to these changes, though a definitive consensus on its meaning is still developing, akin to the ongoing discussions around GEO, AEO, and AI SEO. A definition proposed in the Reuters Institute's 2026 trends and predictions report describes liquid content as "content or stories that are not static but adapt in real time based on the viewer’s context, location, time, or interaction." Artificial intelligence plays a key role in facilitating this by tailoring content to individual user preferences. This necessitates a move for traditional media companies away from authoring discrete "articles" towards developing more flexible, atomic content objects. The foundational elements of traditional articles—verified information, quotes, data, and resources—remain valuable. However, instead of being confined within a rigid article structure, these components are now being integrated into flexible content delivery pipelines. The emphasis is shifting from the article as a monolithic entity to the intrinsic value of the facts and figures it contains. Publishers are being encouraged to focus on becoming the trusted brand that AI recommends, understanding where their brand appears in AI search results, identifying competitor strengths, and strategizing to become the definitive answer provided by AI.

Multimodal content is closely related to liquid content and is sometimes used interchangeably. It is more accurate to consider multimodal content as the dynamic flow of information that constitutes liquid content. This includes various forms of media such as text, images, audio, and video, which can be combined and presented in adaptive ways. The integration of multimodal elements allows content to be more engaging and contextually relevant to individual users. For instance, an AI could dynamically assemble a news report using text summaries, relevant video clips, and audio commentary based on a user's stated preferences or inferred interests. This approach moves beyond the linear consumption of a traditional article, offering a more personalized and interactive experience. The ability of AI to process and generate multimodal content is central to the realization of liquid content, enabling a more fluid and responsive information ecosystem. Publishers aiming to thrive in this new environment must embrace strategies that leverage AI to create and distribute content that is not only accurate and verified but also adaptable and engaging across multiple formats and contexts.