What to Do Now That AI Overviews Turned Search into Reading Sessions

For years, the golden rule of SEO has been to align content with user intent. We categorized queries into buckets, like informational or transactional, and built pages to satisfy those specific needs. It was a predictable system. But the introduction of AI Overviews (AIO) has fundamentally altered how people actually behave on the search results page. The intent is still there, but the behavior has shifted. A useful companion note is structured data, because it looks at a nearby part of the same system.

When an AI Overview appears, it doesn't just provide an answer, it changes the rhythm of the search session. It compresses different types of intent into a single, slower reading pattern. This means the old assumptions about how quickly a user clicks through to a site are no longer reliable. We are moving from a world of quick navigation to a world of SERP reading sessions.

A new mental model for search intent

Recent analysis of clickstream data from roughly 846,000 search sessions in the US reveals a striking change. In a traditional search environment, time spent on the search engine results page (SERP) was closely tied to what the user was looking for. Navigational searches, where someone is looking for a specific brand or site, were fast. Informational searches, where someone is researching a topic, were slower.

The data shows that without an AI Overview, this pattern holds true. For instance, only 12 percent of navigational searchers stay on the SERP after 21 seconds, while 32 percent of local searchers remain. The intent dictated the speed of the exit. The same pattern also shows up in pipeline gates, where the practical question is how the signal becomes visible.

However, when an AI Overview is present, this distinction almost entirely disappears. Between 42 and 48.5 percent of users stay on the page after 21 seconds, regardless of whether their intent was navigational, local, or informational. The AIO acts as a gravity well, pulling every type of searcher into a reading session.

Expert Interpretation: This shift is critical because it breaks the "fast track" advantage of brand recognition. Previously, if you had strong brand equity, users would click your link almost instantly. Now, even those users are pausing to read the AI generated summary first. The tradeoff here is a loss of immediate traffic in exchange for a more informed user, but the decision for operators is clear: you can no longer rely on brand loyalty alone to bypass the SERP reading phase. You must now compete for attention even against your own brand name.

Why intent compression matters

For two decades, the search query was a reliable signal of user behavior. If someone typed a brand name, they were in and out in seconds. If they searched for the best CRM for startups, they would settle in for a comparison session. Intent sorted the traffic into predictable lanes.

AI Overviews have erased those lanes. By placing a block of synthesized text at the top of the page, Google forces every searcher into a reading session. The person looking for a specific login page and the person researching a complex product are now behaving the same way. They both slow down, they both stay on the page longer, and they both consume the AI summary before deciding where to go next.

most users did not choose this. They are not necessarily AI early adopters, but they are being guided into this behavior by the interface. This passive shift in behavior is significant, especially considering that over 1.5 billion people are now using AI Overviews. It is no longer a niche feature, it is the new standard for how the web is searched.

Expert Interpretation: The real danger here is the "zero click" reality, but the opportunity lies in the "slow down." When users spend more time on the SERP, they are more likely to be critical of the results they eventually click. The tradeoff is that the barrier to entry for a click has risen. The decision you need to make is whether to optimize your content to be the source the AI cites, or to optimize your listing to be the most attractive destination after the AI has already provided the answer.

Winning the second impression

Because users are spending more time reading the SERP, the concept of the "second impression" becomes vital. The first impression is the initial scan. The second impression happens during the back scroll, after the user has read the AI Overview and is now looking for a place to dive deeper.

Think of it like a shopper in a grocery store cereal aisle. They scan all the boxes quickly, then they circle back to reread the specific box that caught their eye. In search, metadata is the trigger for that first scan, but it is often not enough to convert a user into a click during the second pass. To win the second impression, your listing must project immediate relevance and trust.

Expert Interpretation: Most SEOs focus on the first impression, which is about visibility and ranking. However, in an AIO world, the second impression is where the actual conversion happens. The tradeoff is that you cannot simply "keyword optimize" your way into a click. You have to provide visual and data driven cues that signal the page is worth the time. The decision here is to shift focus from mere visibility to "click worthiness" during the back scroll.

Optimizing product detail pages

For product pages, the second impression is a comparison game. Users are looking at star ratings, the number of reviews, price, and whether the item is in stock. If your listing is missing these details, it looks empty compared to a competitor who has them all.

To control this, you need to prioritize product schema. Specifically, you should ensure that aggregateRating, review, offers, and availability are all present. If you miss one, your competitor's listing will look more complete and trustworthy. review count is a primary comparison field. A product with 47 reviews will almost always lose to one with 2,300 reviews on the second pass, even if the product description is better.

Review velocity is a competitive moat in this environment. providing multiple images in the schema array gives Google more options to fit different SERP layouts, increasing the chance of catching the eye during that second look.

Expert Interpretation: The technical implementation of schema is a baseline, but the real battle is the data within it. The tradeoff is between spending resources on copywriting versus spending resources on review acquisition. The decision is clear: review volume and velocity are now more important for SERP conversion than the actual text of the meta description.

Optimizing category detail pages

Category pages face a different challenge because they often compete directly with the AIO's own lists. If the AI Overview already lists five top options, your category page must position itself as the place where the user goes to actually make the final choice between those options.

Using ItemList schema is essential here, as it allows Google to render product carousels. A carousel takes up more vertical space than a standard listing, which makes it much more dominant during the back scroll. You should also focus on making your filter and sort UI visible in the SERP preview. This can be achieved by internal linking to specific facets, such as "by price" or "by brand," which makes them eligible to appear as sitelinks.

The depth and page count of the category also matter. A page with a strong selection of products signals to the user that this is a complete hub for decision making, rather than just another list.

Expert Interpretation: The goal for category pages is to move from being a "list of links" to being a "decision tool." The tradeoff is that you are competing with the AI's ability to summarize. The decision you must make is to emphasize the utility of your page, such as advanced filtering and sorting, which the AI cannot yet replicate in a static summary.

Optimizing blog content

With blog content, the AI Overview has often already given the user the answer they were looking for. To earn a click now, you aren't selling the answer, you are selling the validation of that answer. The user wants to know who said it and when they said it.

Credibility is the primary driver here. This means ensuring that the datePublished or dateModified is clearly visible in the SERP. A user is far more likely to click a 2026 article than a 2024 article when the AI has already provided the basic facts. using Article schema with a named author field that links to a sameAs URL, such as a LinkedIn profile or a detailed bio page, is critical. This turns the author into a resolvable entity for Google, which supports E-E-A-T scoring.

Expert Interpretation: The role of the blog has shifted from "providing the answer" to "providing the authority." The tradeoff is that short, answer based posts are now almost entirely captured by the AIO. The decision for content creators is to pivot toward deep dive analysis and opinionated expertise that cannot be synthesized into a few bullet points by an AI.

What intent compression means for operators

It is easy to feel that the last few years of intent based content strategy were a waste, but that is not the case. Intent still dictates what you need to write to be relevant. The shift is not in the content itself, but in the prediction layer on top of that strategy. We can no longer predict how long a user will stay or where they will look based on intent alone, because the AIO now drives that behavior.

Practical next steps

The useful part is not only the idea itself, but the operating habit behind it. Use it as a checklist for decisions: what deserves attention now, what should be monitored, what needs a stronger evidence base, and what can wait until the system has more scale.