Jarrett Sidaway
CEO & Co-Founder, FetchRight
A profound shift is underway in how people find information. Users are no longer navigating homepages, browsing category pages, or scanning search results. Increasingly, they are asking questions directly — and receiving synthesized answers from AI systems that pull from a wide range of sources in real time. This movement from pages to answers represents not just a new interface, but a new discovery paradigm.
For publishers, the implications are enormous. The audience has already migrated to AI-driven discovery channels. The question is no longer whether publishers should participate, but how they participate — and whether they do so on their own terms.
This transition brings risk, but it also brings a rare opportunity: the ability to define how expertise enters AI ecosystems, how that expertise is represented, and how value is created and captured. Publishers who simply hope that AI will "find" their content risk being reduced to background noise. Publishers who structure and govern what they contribute can become essential, high-value partners in the AI economy.
The difference between those outcomes is not determined by algorithms alone. It is determined by strategy.
For decades, publishers measured their reach through traffic patterns shaped by search engines, social networks, newsletters, and direct visits. While those channels still matter, they are no longer the dominant starting point for many users. The shift toward AI-based assistants, copilots, and answer engines reflects a deeper behavioral change: people want immediate, contextualized answers, not lists of places where those answers might exist.
In this new environment, the user's intent is no longer implicit. It is explicit. They ask a fully formed question. They expect a precise answer. And they assume that answer will be accurate, trustworthy, and complete.
This creates a discovery environment where editorial expertise is immensely valuable — but only if the system knows how to retrieve it, interpret it, and present it at the right moment.
If publishers do not shape that process, AI systems will approximate it. They will guess at which sources are authoritative. They will infer structure where structure does not exist. They will pull together fragments of content into answers that may be "good enough," but not representative of the publisher's expertise or voice.
The opportunity for publishers is to replace guessing with governance — to make their authority explicit, not incidental.
Many publishers assume that if they create high-quality content, AI systems will naturally surface it. This was the implicit contract of early SEO: high-quality content, properly optimized, would earn its place in search results.
AI breaks this assumption.
AI systems do not rank pages; they reconstruct answers. They pull from multiple sources, weigh semantic relationships, and assemble responses that may incorporate — or overlook — a publisher's most important insights. If the content is unstructured, or if the use rules are undefined, the AI system fills in the gaps algorithmically.
In other words, publishers cannot rely on the system to "understand" them unless they deliberately encode how their content should be understood.
This requires:
Publishers must design their presence in AI ecosystems as intentionally as they designed homepages or mobile apps. The answer layer is the new distribution layer, and distribution has always required strategy.
AI-driven discovery offers an advantage that traditional web discovery never could: publishers can know the user's intent in extraordinary detail.
In search-based environments, intent was deduced. Keywords were proxies. Clicks were signals. Dwell time was data to reverse-engineer.
In AI environments, intent is spoken. The user tells the system exactly what they want. That is a gift — if publishers know how to use it.
When you know the question, you can deliver the answer that best serves that intent. Not the full article. Not the generic summary. The specific insight that meets the user where they are in their decision-making or learning journey.
This is why publishers must think beyond "making content available to AI." They must think in terms of matching content to intent, with the precision that AI now allows. It means serving different versions of the same expertise for different use cases:
This precision transforms AI discovery from an external threat into a channel for acquiring and engaging audiences on terms that reflect the publisher's strengths.
But precision is impossible without structure. And structure is impossible without control.
When AI pulls from unstructured content, it sees the text but not the hierarchy of meaning that a human editor would recognize intuitively. It may choose the wrong paragraph, ignore the essential qualifier, or pull an outdated claim into a contemporary answer. Each of these outcomes dilutes the publisher's authority.
Structuring content solves this. It enables publishers to declare:
This is not rewriting content for AI. It is expressing editorial intent in a format AI can reliably interpret.
With structure, AI systems can retrieve publisher expertise accurately. Without structure, they attempt to infer it — and in inference lies the risk of error.
For publishers who care about authority, accuracy, and brand integrity, that difference is existential.
The control required for this strategy cannot live inside the CMS or at the page level. By the time an AI crawler reaches those systems, it has already retrieved parts of the content. Governance must happen before the access occurs — at the edge of the publisher's domain, where requests enter through the CDN.
At the edge, publishers can:
This is where FetchRight operates — not inside the CMS, not as another workflow, but as infrastructure that translates publisher rules into enforceable interactions with AI systems.
When control is placed at the edge, strategy becomes operational.
Most conversations about AI and publishing are framed around loss: loss of traffic, loss of attribution, loss of business models. But the precision that AI allows can also create growth where it did not previously exist.
If a user enters an AI system with a high-intent question — a product comparison, a medical concern, a financial decision, a legal nuance — and the publisher provides the exact insight that answers that question, the publisher can influence the user's next step.
This influence might take the form of:
Precision is not just a defensive tool. It is a revenue and engagement strategy rooted in matching the right expertise to the right moment.
AI does not eliminate the publisher–audience relationship. It changes where that relationship begins.
AI-driven discovery is not a future scenario. It is a present reality. Audiences have already shifted their behavior. Platforms have already shifted their design. The only question is whether publishers will shape this new landscape or allow others to define it for them.
The publishers who treat AI as a threat will retreat into blocking, litigation, and isolation. The publishers who treat AI as an opportunity will build infrastructure, establish rules, define structure, and let their expertise travel into the answers users rely on.
Visibility, control, and precision are now the essential ingredients of influence.
FetchRight exists to give publishers the tools to participate in AI discovery on their terms — with structure, integrity, and strategic intent. But the decision to lead belongs to the publishers themselves.
Those who build their presence deliberately at this pivotal moment will define not just how answers are made, but how audiences come to trust and depend on the brands behind them.
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.
When discovery moves from pages to answers, the value of expertise increases. Publishers have an opportunity not just to participate in the AI ecosystem, but to shape its trajectory.
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.