Jarrett Sidaway
CEO & Co-Founder, FetchRight
Over the past decade, publishers have watched discovery shift beneath their feet. First it moved from homepages to social feeds. Then from social feeds to search. Now, increasingly, it is moving from search to AI-driven answers — a shift that is not incremental, but foundational. For the first time, the dominant interface for information is not a list of links, but a synthesized response.
This evolution has created understandable uncertainty across the publishing world. But it has also created something that publishers rarely receive in disruptive moments: leverage.
Because when discovery moves from pages to answers, the value of expertise, authority, and verified information increases — not decreases. AI systems rely on high-quality publisher content to function responsibly, and they cannot manufacture that quality on their own. Yet in the absence of structure, clarity, and standards, these systems are forced to approximate the meaning of publisher insights rather than understand them.
This is where publishers have an opportunity not just to participate in the AI ecosystem, but to shape its trajectory.
The future of discovery will be defined not by those who chase algorithms, but by those who define how their content is interpreted, licensed, and presented in the AI environments where audiences now look for answers.
In the traditional web economy, distribution was everything. Visibility depended on SEO performance, link structures, recirculation loops, social algorithms, and the optimization of headlines and page layouts. Publishers built teams, tools, and strategies dedicated to distributing content into channels they did not control.
AI changes this paradigm entirely. Answer engines do not reward click-through rates or dwell times. They do not prioritize page layouts or social engagement signals. They operate on a different logic: they interpret content, break it into components, embed it semantically, and reconstruct it to answer a user's question directly.
This shift turns publisher content from a destination into an input, and it places enormous emphasis on how well that content can be understood by an AI system. In this model, the winners are not those who chase distribution hacks, but those who structure their content intentionally for machine-level interpretation.
This is not about rewriting editorial judgment for AI. It is about ensuring that a publisher's authority and expertise survive the translation layer — so that AI discovers not just text, but meaning.
There is a misconception that AI may eventually replace the need for publishers altogether. But the opposite is true. As AI systems grow more powerful, their dependency on accurate, timely, high-integrity information grows with them. No model, regardless of scale, can generate truth from inference alone. It needs structured signals from authoritative sources.
Publishers provide these signals. Their work undergoes fact-checking, editorial oversight, ethical review, and contextual framing. They produce expertise, not noise — and that expertise becomes more valuable, not less, as AI systems integrate deeper into how people seek information.
Yet today, much of that expertise is being consumed without its context, without its signals of authority, and without its intended structure. AI systems ingest enormous volumes of publisher content but often misinterpret the most important elements: relevance, recency, nuance, editorial intent.
This is not a flaw in AI models. It is a flaw in how content is delivered to them.
If publishers want AI to treat their work as authoritative, they must provide that work in a form that preserves its authority. That requires structure — not just in the text itself, but in the relationship between publisher and platform.
In the early web, publishers learned to adapt their content for search engines — using metadata, sitemaps, internal links, and schema markup to guide discovery. AI requires a different form of adaptation. It needs clarity of rights, transparency of access, and content formats that align with how AI systems actually read information.
This includes structured summaries, definition blocks, fact panels, named entities, updated signals, and domain-specific transformations. None of these replace traditional editorial work. Instead, they are mechanisms that ensure AI systems can process that work with fidelity.
Structuring content for AI is not a technical exercise. It is a strategic one.
For publishers, it enables:
For AI platforms, it enables:
For consumers, it enables:
When publishers structure their content for AI, they are not bending to a new distribution channel — they are elevating the role of their expertise within it.
It is tempting to view AI platforms as extractive forces — systems that take publisher content without permission or compensation. And in many cases today, that characterization is justified. The current crawling environment lacks rules, transparency, and enforceable agreements. But extraction is not inevitable.
When publishers define the structure, format, and terms under which their content is accessed, the dynamic shifts from extraction to collaboration. AI platforms gain clarity. Publishers gain control. And the ecosystem gains stability.
The absence of structure is what makes AI feel extractive today. The presence of structure is what enables a mutually beneficial relationship.
This is the philosophical foundation of what FetchRight enables: a system in which publishers determine how their content participates in AI discovery, and AI platforms gain the structured, rights-cleared inputs needed to deliver accurate, high-quality answers.
For the first time in a decade, publishers are not being asked to react to a platform shift — they are being invited to define it. AI cannot progress without high-quality content. And high-quality content does not exist without the publishers who create it. This gives publishers both leverage and responsibility.
Editorial leaders should not simply be asking, "How do we protect ourselves from AI?" They should be asking:
These are questions of leadership, not compliance.
Publishers who lead will design the next era of discovery. Publishers who wait will find themselves optimized out of it.
FetchRight is built on the belief that publishers should not compete with AI, but shape it. The platform provides the infrastructure for publishers to deliver structured, rights-cleared content tailored to AI retrieval use cases. It gives publishers the ability to define what AI can access, how it should interpret that content, and under what terms it may be used. And it ensures that their voice — their true editorial voice — survives the translation into AI-generated answers.
This is not a defensive posture. It is an offensive strategy. It positions publishers not as sources of raw material, but as partners in a new form of discovery that will define how people consume information for decades to come.
The next era of discovery will not reward those who create content alone. It will reward those who make their expertise legible, accessible, and authoritative within AI environments. Publishers already have the most important asset — trusted information. What they need now is the structure and strategy to ensure that information shapes the AI-driven world.
AI is not the threat. Unstructured participation is. Publishers who choose to lead — by defining how their content is understood, licensed, and delivered — will shape not only their own future, but the future of how knowledge circulates in society.
The audience has migrated to AI-driven discovery channels. Publishers who structure and govern what they contribute can become essential partners in the AI economy.
AI upends the logic of pages as the atomic unit of value. Publishers can allow their content to be atomized without input, or they can define how their expertise is represented in the new answer layer.
Publishers' biggest readers are no longer human — they're AI systems. Yet most publishers have no visibility into this interaction. Closing that gap is the first step toward deciding how AI should use your content.