How websites can adapt to generative search interfaces

Generative search interfaces embedded in AI-powered search engines generally don’t replace the search engines underneath them. For instance, in Yandex Search, Alice AI still draws on indexed, ranked pages to synthesize its answers. Technical SEO still matters, but it is just the baseline, one part of a much bigger picture. Ranking competitively among generative interfaces now takes everyone from product and content teams to PR professionals.

There was a period when simply publishing content or fixing the basics of a site was sufficient to thrive online. Every category now has more content, more services, and more products competing for the same attention. The fundamental shift is this: search no longer needs to find something that is simply “relevant.” Instead, it now needs to identify the best among many relevant options and synthesize them into a single, coherent answer. This shift changes how websites should think about their role in the online ecosystem.

Visibility is now everyone’s job

For several years, search visibility was treated as the responsibility of a specialist who managed keywords, monitored rankings, and tweaked meta descriptions. That model is both outdated and limiting. Search performance is now shaped by the quality of a product, the clarity of a value proposition, the credibility of the content, the trust signals built across third-party platforms, and the conversion experience a user encounters after clicking through.

Technical SEO still matters, because a site that search engines cannot crawl, parse, or trust will not perform regardless of how brilliant the content is. Think of technical SEO as the sign above a shop door. It has to be visible and easy to read, but a great sign doesn’t make you the best shop around — that comes down to what’s inside. Once the technical baseline is met, the real question becomes whether the source actually solves the user’s problem better than everything else available.

Product managers, UX designers, editorial leads, PR professionals, and marketing teams all influence whether a page earns a place in a generative answer. Brands that treat visibility as a shared responsibility may be better positioned than those that don’t.

The website is no longer the whole brand

Users decide which surfaces they trust

One of the more consequential changes in search behavior is that websites have lost their monopoly over brand representation. Users build trust across many surfaces, including independent bloggers, social platforms, review sites, and the AI-generated summaries that draw upon all of them.

Businesses need to think more expansively about their brand footprint and distribution. Owned content, media collaborations, expert authors, offline formats, and platform-native content can all be legitimate parts of that footprint if they are honest, high-quality, and genuinely useful to users. 

The need for external content investment

It is difficult for a company to objectively compare itself to competitors on its own site, because readers know the brand has a vested interest. An independent author, a respected blogger, or an established media outlet making that same comparison reads as more credible. If that third-party content is factually accurate and useful to someone evaluating options, it becomes a strong candidate for citation.

Getting cited in a generative answer is not a shortcut to conversion, though — it is a single touchpoint. It may influence trust or consideration, but it does not magically compress the funnel. Conversion still depends on the value of the offer.

EPOS: what it means to be reference-worthy

Covering a topic is no longer the same as solving it. Generative systems aim to resolve a user’s actual task, which is rarely as simple as finding relevant information about the topic. Users are comparing options, validating a decision, or trying to complete a specific action. Yandex has developed its own EPOS framework for what makes content reference-worthy in generative search: Expertise, Practicality, Originality, and Substance.

Expertise

Content should demonstrate that it comes from someone with direct expertise in the subject. Authors should have real credentials, real experience, and a track record that signals expertise to both readers and generative systems. AI-assisted content creation has a real boundary here. Using AI as an editorial tool is fine, but replacing expert authors with generic AI-generated output damages the trust that reference-worthiness depends on.

Practicality

Content should address the user’s actual task, not just match keywords without solving the need behind them. Websites should publish content that answers not only the real question behind a user’s query, but also the related questions an AI-powered search engine may ask while generating its answer.

Users are constantly looking for things: where to travel, what to buy, which performance to see, how to solve a practical problem. They need content that directly addresses and resolves these concerns.

Originality

Content with a genuine point of view, original data, or a unique perspective not available elsewhere will stand out from generic content. Aggregated and repackaged information is easy to deprioritize when many sources say the same thing, so websites should focus on saying something users and generative engines can’t get anywhere else.

Substance

Topical depth matters more than length. Evidence of reputable sourcing, factual detail, and real follow-through on a topic are more likely to stand out from pages that only skim the surface. A page that performs well in organic search but doesn’t show up in generative answers may simply not be covering the topic with enough depth or factual detail for synthesis to draw from.

How sources get selected

How AI-powered search engines select sources is broader than classic organic ranking for a single query. For example, Alice AI can expand a query into multiple related questions and draw on sources that cover those adjacent angles well when generating an answer.

Websites should plan for that pattern broadly. Deep, factual, well-structured coverage of a topic is useful not only for the query a user actually submitted, but for the related, fanned-out questions a generative system like Alice AI might use on its way to an answer.

The one rule that never changed

The way I see it, generative search is a new interface layered on top of existing search infrastructure, and the same principle still applies: the best result is the one that solves the user’s task. What has changed, though, is the breadth of that task and the level of competition for it. Websites that want to adapt need to know their audience, understand what they’re trying to accomplish, and create content that’s genuinely useful to them.

Author Bio

Author: Mikhail Slivinskiy

Author Bio:

Mikhail Slivinskiy is Search Ambassador at Yandex with over 15 years of experience in search technology and SEO. At Yandex, he has worked across product development, webmaster tools, and publisher engagement, including leading Yandex Webmaster from 2017 to 2024. He now focuses on how AI-driven search is evolving and how businesses can maintain visibility through authoritative content.