What is AI Overview? (Google’s AI Search Feature)

When a user, like yourself, types a query into Google Search these days, what comes back isn’t only a list of blue links. For many searches, Google now shows an AI Overview, a generative AI-powered summary of a search query, combining info from multiple web sources to provide a coherent answer or explanation.

The AI-generated “overview” usually appears above the organic search results (sometimes even above ads). For many users in supported countries/languages, it appears automatically for search queries that Google deems “information-rich” or where summarization adds value.

From Search Generative Experience to AI Overviews

AI Overviews, or AIOs for short, didn’t come about overnight. The roll-out was gradual. Here’s how it played out:

How AI Overviews Work

Behind AI Overviews’ capabilities is the Gemini family, Google’s flagship suite of multimodal large language models. Unlike earlier models, Gemini can process text, images, audio, and even code. By mid-2025, Google had begun using Gemini 2.5, particularly its Flash and Pro variants, to power AI Overviews in the United States, giving the summaries improved reasoning and faster responses.

Gemini itself is the successor to PaLM 2 and LaMDA. It was trained on diverse data types and is designed with flexibility in mind: lighter, speed-optimized versions like Flash handle quick, everyday queries, while more powerful variants such as Pro and Ultra step in when a search requires deeper reasoning.

To keep the generative answers grounded, AI Overviews use a retrieval-augmented generation (RAG) process. Instead of relying solely on the model’s internal training, which risks hallucinations, Google’s systems pull in real content from the web.

While not perfect (hallucinations and incorrect responses still occur), the RAG process refers to relevant sites, extracts snippets, and those details are woven into the generated summary. The retrieval process leans on Google’s existing search infrastructure. Indexing, ranking signals like quality, relevance, and freshness, and structured data from the Knowledge Graph all still matter.

Triggers and Criteria

So, what kinds of search queries tend to trigger AI Overviews? In most cases, it is informational or explanatory questions, the classic “What is X?” or “How does Y work?” type searches, where a user benefits from seeing information summarized across multiple sources.

Google’s own Help pages note that Overviews appear “when our systems determine that generative AI can be especially helpful – for example, when you want to quickly understand information from a range of sources.”

Complex or multi-step queries also regularly trigger AIOs, since they often require synthesis rather than a single fact. Subjects that lean heavily on knowledge, such as science, history, or technical comparisons, are more likely to trigger Overviews than transactional queries like “buy X,” although there can be overlap.

On the other hand, there are clear situations where AI Overviews are less likely to appear.

Very simple fact lookups are usually better served by a direct answer box, featured snippet, or Knowledge Panel. Queries that are highly location-sensitive may be excluded to avoid generic or misleading summaries.

Similarly, searches tied to breaking news or highly subjective topics are less suited to AI Overviews, since the underlying information may shift too quickly or lack a reliable consensus.

Presentation and Features

AI Overviews usually take the form of a summary block with a heading, followed by a synthesized text answer that draws on multiple sources. Beneath or within the text, users see links to supporting websites.

To improve clarity, Google has been experimenting with “in-line links” placed directly inside the overview text and with small icons or site badges. On desktop, these supporting links may also appear in a right-side panel, while on mobile, tapping icons or the “see more” option reveals additional sources.

Over time, the presentation has been tweaked and refined. Google has worked to make supporting web links more visible and prominent, giving users clearer pathways back to the original content. In certain queries, especially on mobile in the U.S., ads may also appear in association with AI Overviews, although they are labeled to distinguish them from organic content.

The entire design has been tuned for speed and responsiveness so that answers load quickly without breaking the familiar rhythm of Google Search.

Despite these improvements, there has been considerable pushback against AI Overviews by both users and site owners, which I’ll touch on in just a moment.

AI Overviews vs. AI Mode: What’s the Difference?

Real quick, though: Don’t get AIOs mixed up with AI Mode. They’re separate features.

AI Mode represents a more interactive, conversational tier of Google Search powered by generative AI, beyond what AI Overviews provide. While AI Overviews give you a concise summary of a query, drawing from multiple sources and surfacing key points, AI Mode enables a deeper engagement.

It allows follow-up questions, handles more complex, layered prompts, and supports multimodal inputs (text, voice, images).

Under the hood, AI Mode is built with more powerful variants of Google’s Gemini model (e.g., Gemini 2.5 Pro), using techniques like “query fan-out,” where the system breaks a user’s question into subtopics and searches many sources concurrently.

The result is a richer, more detailed response, often with categorized insights, side-by-side comparisons, or even deeper researched reports when required.

Challenges, Concerns, and Limitations

Quickness and convenience come with risk. Errors, sometimes bizarre ones, aren’t uncommon when it comes to AI Overviews. For instance, Google-AI Overviews have mistakenly suggested adding glue to pizza sauce to help cheese stick better, pulled from a satirical Reddit post.

In another case, an Overview implied that tobacco had health benefits for children, echoing outdated and debunked claims. Others have misquoted history, like confusing John F. Kennedy with Lyndon B. Johnson in accounts of the moon landing, or giving unsafe health advice, such as encouraging people to eat rocks for minerals.

There was even an example where the system recommended that pregnant women drink urine to ease nausea, a claim sourced from a joke forum.

These instances illustrate how generative AI can mislead when the source data is ambiguous, satirical, just plain wrong, or the AI simply makes a mistake.

Impact on Traffic and Revenue for Websites

If users are getting the answer to their queries directly on the SERPs, where does that leave websites, particularly those that chase informational keywords?

It’s not looking so great, to be honest. Uh-huh, there’s data showing that the presence of Overviews significantly reduces click-through rates (CTR) to traditional organic search listings.

For example, a recent Ahrefs study found about a 34.5% drop in CTR for position 1 when an AI Overview is present. Non-branded informational queries are hit hardest. Google is pushing organic blue links lower on the page, which means even pages that rank well may see dramatically fewer visits.

Yeah, not great news.

There is some silver lining, though: Being cited in an AI Overview or having content that feeds into those summaries is increasingly valuable.

Google may “source” your content in its overviews, which may help maintain visibility even if fewer users click through. However, there’s also tension: some publishers argue that this reduces their opportunity to monetize content via ad views or affiliate links when users get their answer without visiting the site.

It really just depends on a site’s niche and monetization strategies.

Regional and Language Gaps

Google has rolled out AI Overviews to many regions and multiple languages, but the feature remains experimental or opt-in in some places. That means in certain countries or for certain languages, users still won’t see Overviews at all, or will see limited / lower-quality versions.

These gaps magnify other limitations: non-English content tends to have less robust source material, less brand recognition, and sometimes more unreliable or less moderated input data.

The risk is that users in underserved languages or regions get poorer summaries or find Overviews less trustworthy. For publishers serving those markets, it’s harder to be cited or treated as authoritative because the data foundation in those languages may be thinner.

Future of AI Overviews and Search

Google is actively pushing for an AI-first future, moving its features from basic summarization toward more agentic behaviour, wider language support, multimodal inputs, and deeper integration into its Search experience.

From what’s public, Google I/O 2025 and follow-ups have made clear that agentic capabilities are a major part of the roadmap. Agentic AI refers to systems that can perceive, reason, plan, and act with more autonomy and less micro-direction from users.

For example, Gemini is being used to build “agents” that can take actions on behalf of users, such as filtering, comparing, or toggling between tasks, especially in Search, Chrome, and via the Gemini app. These agents are designed to “see” via camera, understand context, and interact across apps. (Observer)

Google is also expanding its language footprint and country availability. As of May 2025, AI Overviews are available in over 200 countries and territories, and in more than 40 languages, including Arabic, Chinese, Malay, Urdu, and more. The expansion is aimed at bringing AI Overviews to more native languages and familiar languages.

Multimodality is increasingly being pushed out by Google as well. The company is not just expanding languages but also expanding the kinds of inputs (and outputs) it can handle, audio, images, and video, to make Overviews more interactive and useful in varied contexts.

For instance, tools like NotebookLM are introducing “Audio Overviews” in many languages. Multimodal AI helps the system understand context beyond just query text, which could make Overviews more robust and usable in real-world, messy scenarios. (cloud.google, marktechpost.com)

Lastly, things like “AI Mode” are being developed so users can choose more AI-centric results, possibly defaulting to them. Google is introducing more queries that are complex, multi-turn, and conversational. The idea is that Search can shift not just to provide summaries but be more of an assistant, responding over multiple steps, pulling in varied content, even doing reasoning.

Yeah, there’s so much going on.

Love it or hate it, AI features are being rolled out and integrated across Google’s ecosystem, and that doesn’t seem to be something that’ll slow down anytime soon.

Conclusion and Next Steps

Here’s your TL;DR:

1. AI Overviews = Google’s AI-generated summaries that sit above blue links
2. Users get fast, convenient answers ,but risk missing nuance or accuracy
3. Websites see fewer clicks when Overviews appear

The future of SEO is no longer just about ranking number one, but about becoming the reference that powers AI responses.

The good news for you is that we specialize in LLM-driven SEO strategies designed to keep your content visible in a world of AI-generated summaries.

Simply head over to our LLM SEO services page to find out how we can help you not just rank, but be cited.