AI SEO + SEO for AI: AI Overviews & Zero-Click Searc

Search hasn’t “killed” SEO. But it has re-scoped it.

A few years ago, if you ranked well for the right keyword, you could reasonably expect a click. Today, the default outcome of many searches is consumption inside the results page—through rich SERP features, interactive modules, and AI-generated summaries.

A 2024 clickstream-based analysis of U.S. and EU Google searches reported that 58.5% (U.S.) and 59.7% (EU) of searches resulted in zero clicks (no click on any result). At the same time, a large share of clicks that do happen stay inside Google-owned properties, and only 360 (U.S.) and 374 (EU) clicks per 1,000 searches went to the open web in that study.

That’s why the real question isn’t whether SEO still matters. It’s which kind of SEO you’re doing now:

AI-assisted SEO: using AI tools to scale research, drafting, analysis, and workflow.
SEO for AI: engineering your brand and content so AI layers (AI Overviews, AI Mode, and other AI answer systems) can select, trust, and cite you—often before a user ever considers clicking.

This article is designed to be a true “everything in one place” resource: the strategy shift, the mechanics behind AI search visibility, how to publish content that survives and wins in feature-heavy SERPs, how to build trust with EEAT, and how to measure success when clicks are no longer guaranteed.

The SERP became an ecosystem, not a list

Modern SERPs are not “10 blue links.” They’re interfaces that mix multiple content types, formats, and intent layers. Instead of a list, the results page behaves like an ecosystem of modules—each competing for attention and often satisfying the query without a website visit.

A Semrush Sensor snapshot (U.S. desktop) found that only 1.19% of SERPs showed no SERP features at all, meaning nearly every results page included at least one attention-stealing module. In that snapshot, common features appeared at high rates, including:

People Also Ask ~67.79%
Images ~50.63%
Video ~46.65%
Knowledge Panels ~23.83%
Local Packs ~17.62%
AI Overviews listed at ~8.19% frequency in that view

This matters because the SERP is now a competitive surface area problem. You are not only competing for rank. You are competing for presence across modules that can satisfy the query without a site visit.

Academic research supports what practitioners feel: SERP features are not cosmetic. A 2023 study (“Beyond Rankings”) analyzed 67,000 keywords, 24 SERP features, and millions of clicks/views, concluding that SERP features can significantly modulate CTR—amplifying or attenuating traffic beyond ranking position alone.

The strategic implication is simple: ranking is still valuable, but rankings alone are no longer a complete visibility strategy. A strong SEO program must deliberately target SERP real estate (snippets, PAA, image/video surfaces, local modules) and not treat them as side effects.

Why clicks are down and why that changes the SEO job

If the SERP is an ecosystem, then clicks become a scarce resource. Multiple high-quality studies show that scarcity is real.

Zero-click behavior is now “normal,” not exceptional

A large clickstream study (U.S. + EU panels) reported 58–60% of Google searches ended with zero clicks in 2024, and only ~36–37% generated clicks to the open web (360–374 per 1,000 searches, per that study). Even within the remaining click share, a substantial portion goes to Google-owned surfaces rather than independent sites.

This means many informational queries now behave like a knowledge consumption activity rather than a website discovery activity.

AI summaries correlate with fewer outbound clicks

Pew Research Center analyzed browsing behavior from March 2025 and found that when an AI summary appeared:

users clicked a traditional search result link in 8% of visits, versus 15% when no AI summary appeared
users clicked a link inside the AI summary only 1% of the time
users ended their browsing session more often (26% with an AI summary vs 16% without)

Independent of AI summaries, Pew also found that around two-thirds of searches resulted in users either staying on Google or leaving without clicking a search-result link.

CTR decline is measurable at scale

Industry studies—while not as methodologically universal as clickstream panels—consistently show direction: informational CTR is being compressed by AI features and by feature-heavy SERPs.

Ahrefs has reported measurable CTR reduction when AI Overviews appear (with updated analyses into late 2025 and beyond).
Seer Interactive has published repeated updates showing CTR compression patterns on keywords with AI Overviews.
Search Engine Land has summarized those findings and broader CTR decline patterns across informational SERPs.

These aren’t just “SEO metrics.” They’re signals that the SERP is capturing more user value before visits occur, and that the SEO function must expand from traffic acquisition to attention capture and trust placement inside the interface.

Important nuance: AI Overviews do not behave identically across intents

A high-quality SEO program must avoid simplistic conclusions like “AI Overviews always reduce clicks.”

Semrush analyzed a large dataset of keywords and clickstream signals and reported that:

AI Overview presence peaked near ~25% in July 2025 (in their keyword set) and later declined (~15.69% in November 2025), indicating volatility rather than a straight rollout line
the share of AI Overviews triggered by informational queries shifted materially (informational share falling while commercial/transactional share rose)
navigational AI Overviews increased meaningfully in their tracking
for the same keywords before vs after an AI Overview appeared, Semrush reported a decrease in zero-click rate in their analysis, suggesting the relationship between AI summaries and clicks is not one-dimensional

The correct conclusion is not “SEO is dead.” It’s:

SEO has become multi-surface and intent-sensitive, and your strategy must be built around a world where the click is optional.

AI-assisted SEO vs SEO for AI: two disciplines you must separate

Most teams are mixing these two disciplines without naming them. Naming them clarifies what to build, what to measure, and what skills you need.

AI-assisted SEO

AI-assisted SEO is about improving how you produce and manage SEO work.

Google acknowledges that content production can include automated, AI-generated, or AI-assisted processes—and that explaining these processes can be useful to users when expected. But Google’s warning is consistent: using automation (including AI) primarily to manipulate rankings violates spam policies.

So AI-assisted SEO is safest when AI accelerates:

research synthesis
drafting and editing
data compilation and structured outlining
entity extraction and internal linking suggestions

…and then a human layer adds experience, interpretation, decision value, and accuracy.

SEO for AI

SEO for AI is about how your work appears and is represented in AI search layers.

Google documentation describes AI Overviews and AI Mode as features that may use “query fan-out”—issuing multiple related searches across subtopics and data sources—then selecting supporting web pages while generating a response. Google also notes that AI Overviews are shown only when systems determine the feature is “additive,” so they may not trigger for many searches.

In practice, SEO for AI aims to make your content:

eligible (indexed and snippet-eligible)
findable (internally linked and technically accessible)
extractable (structured, clear, scannable)
trustworthy at the entity/topic level (consistent with EEAT concepts)

What Google says it rewards and what it penalizes

The fastest way to make your strategy “more researchful” is to anchor it in what Google has actually published—and connect those statements to observed market outcomes.

Google’s public stance on AI content is value-first, not tool-first

Google has stated that using automation (including AI) to generate content primarily to manipulate ranking is a violation of spam policies. Its “scaled content abuse” concept focuses on producing large amounts of unoriginal or low-value content—“no matter how it’s created.”

This matters because it rejects two myths:

“Human-written = safe”
“AI-written = unsafe”

The real dividing line is value and intent, not the tool.

Helpful content can be operationalized

Google’s helpful content guidance offers self-assessment questions that align closely with what marketers call “content effort,” including whether content provides:

original information, reporting, research, or analysis
a substantial, complete explanation
insight beyond the obvious
additional value beyond copying or rewriting other sources

In an AI SERP world, this becomes a business truth: commodity summarization is not competitive, because the SERP itself can summarize.

EEAT shapes evaluation (but isn’t a checkbox ranking factor)

Google references EEAT (Experience, Expertise, Authoritativeness, Trustworthiness) as a conceptual model used to assess helpfulness. Google also clarifies that quality raters do not directly control ranking and their ratings aren’t used directly in ranking algorithms. Rater feedback is used to evaluate whether changes improve results.

So treat EEAT as a design and quality discipline, not a “ranking hack.”

The Who / How / Why framework is an official quality lens

Google advises evaluating content through three questions:

Who created it (authorship, background)
How it was created (process, testing, evidence)
Why it was created (help users vs attract search visits)

This framework turns your content strategy from opinion into a repeatable system: every page can be evaluated and upgraded using Who/How/Why before publishing.

How AI features select sources and what “synthesis-ready” content looks like

Google does not publish a simplistic “AI Overviews ranking algorithm,” and third-party correlation studies should be treated as directional rather than definitive. However, Google publishes enough to build a practical playbook.

Eligibility and baseline SEO still matter

Google’s documentation for AI features is clear:

to be shown as a supporting link in AI Overviews or AI Mode, a page must be indexed and eligible to appear with a snippet
there are no special technical requirements or special schema required solely for AI features
foundational practices still apply: internal linking, page experience, text availability, quality images/video when relevant, structured data matching visible text

This reinforces the key strategic idea:

SEO for AI is not separate from SEO fundamentals. It’s an extension of them into a synthesis interface.

Query fan-out changes what “coverage” means

If a single user query fans out into multiple implicit sub-queries, “ranking for one keyword” becomes a weaker goal.

Instead, you want to become the best supporting source for one or more subtopics that AI repeatedly retrieves during fan-out.

That changes how you write. Your job is not only to “answer.” Your job is to be the most reliable supporting evidence.

The model that wins: Answer + Evidence + Decision support

AI can summarize. Most AI content fails because it stops at summarization.

To build synthesis-ready pages, structure your content so it contains three layers that are hard to fake at scale:

Answer

A clear explanation a user (and a model) can extract quickly. This is where scannable structure and direct definitions matter.

Evidence

Your proof: original research, real-world testing, screenshots, photos, benchmarks, logs, first-hand observations, or carefully cited primary references.

Decision support

Tradeoffs, scenario-based recommendations, failure modes, and “what to do next.” This is what turns a page into a true resource.

This model can be implemented without fluff. In fact, high-effort content is often clearer and more practical—not longer for the sake of length.

High-effort content patterns that survive AI summarization

Here are patterns that consistently create “resource value” beyond what AI summaries can replace.

Product and tool reviews (SaaS, ecommerce, AI tools)

A “best X” page that survives includes:

test methodology
comparison criteria
results
screenshots or proof of usage
“who it’s for / not for”
decision guidance

This aligns perfectly with Who/How/Why and creates a page AI can safely cite.

Operational how-to guides

Instead of “what is X,” win with:

“how to do X safely, quickly, correctly”
step-by-step instructions
edge cases
troubleshooting
checklists and templates

Decision frameworks (consultant-style content)

High-performing informational content increasingly looks like a professional memo:

If your situation is A → do this
If your situation is B → do that
If your situation is C → avoid both and do this instead

This is what “insight beyond the obvious” looks like.

A caution that strengthens trust: AI answers can be wrong

Synthesis interfaces increase the importance of evidence and clarity because they can create the appearance of authority even when information is incomplete.

Public investigations and reporting have raised concerns about AI Overviews producing misleading guidance in sensitive topics and relying on less authoritative sources in some cases.

For SEO strategy, this is not only an ethical warning—it’s a competitive opportunity:

Brands that publish traceable evidence, methodology, and updated guidance are better positioned to earn trust and citations when query stakes are high.

Where SEO is going and what to measure now

Search is evolving from retrieval to assisted understanding.

Google frames AI Overviews as a way to help users explore and learn, and describes AI Mode as an end-to-end AI search experience that uses fan-out and follow-up questions to go deeper through links.

At the same time, behavioral data suggests users often do not click—especially with AI summaries present.

That shifts measurement from “Did we rank?” to:

“Did we capture visible trust?”
“Did we influence the decision?”
“Did we convert the intent we earned—even if the click happens later?”

Video visibility is no longer optional for many topics

Google’s AI-feature guidance recommends supporting textual content with high-quality images and videos when applicable.

Multiple industry analyses suggest YouTube receives outsized citation presence across AI search experiences. The practical takeaway isn’t “make videos for everything.” It’s:

For queries where demonstration matters—procedures, troubleshooting, product walkthroughs—video is now a core visibility surface. Your SEO program should integrate video into topical authority.

A practical approach:

publish the guide
create a companion YouTube video
embed it on the guide
add chapters + timestamps
include the same decision framework in both formats

The modern KPI stack (what to track in 2026)

Search Console still matters, but rankings alone don’t explain outcomes anymore. A strong KPI stack includes:

Visibility KPIs

impressions (by intent group)
rankings (but segmented by feature-heavy SERPs vs clean SERPs)
SERP feature coverage (PAA, video, images, local, snippets)
AI feature presence and citation visibility (manual sampling + monitoring tools)

Engagement KPIs

scroll depth
time on page
return visits
email signups and micro-conversions

Business KPIs

assisted conversions (first touch was search/AI, conversion later)
branded search growth
lead quality and close rate from organic

This supports a reality: you may win more impressions and fewer clicks, so your economic model can’t rely on clicks alone.

A practical playbook: how to win in AI SEO + SEO for AI

Here is a direct “build this” system you can implement.

Build one pillar resource that is actually citation-worthy

Your pillar page should include:

clear definitions
direct answer blocks
evidence and references
decision frameworks
step-by-step execution guidance
templates/checklists
FAQ section

Then add:

an author box with real credentials
a clear editorial process (“How we research and update this guide”)
updated date + what changed

Create supporting assets inside the pillar

AI systems and humans both love “assets.” Add:

a checklist
a decision tree
a comparison table
a prompt library
a glossary

Assets increase citations, shares, and links.

Structure for extractability

Use a repeating pattern:

direct answer
why it’s true
when it’s not true
steps
example
FAQ

This reduces misinterpretation and makes your content easier to use in AI summaries.

Strengthen your brand entity signals

In a world where AI answers act like a recommender, brand signals matter more:

consistent brand name
consistent author name and profile
About page, Contact page, and proof of legitimacy
consistent profiles across the web (company, founder, social, citations)

30 / 60 / 90 day action plan

First 30 days

publish the pillar guide (this article)
improve About/Contact/Editorial pages
add internal links from top site pages to the guide
create one “asset” inside the article (a checklist or template)

Next 60 days

publish 6–10 supporting articles (subtopics that fan-out would retrieve)
build a video companion for the pillar
start collecting proof (screenshots, mini case notes)

Next 90 days

refresh the pillar using Search Console queries
add 2 mini case studies
build brand mentions (partnerships, PR, collaborations, guest appearances)

Final perspective: what “good SEO” is now

SEO used to be primarily about ranking pages. It’s now about:

owning SERP real estate
being selected as supporting evidence in AI summaries
capturing trust early
building brand recall
converting later (even when the click is delayed)

AI didn’t remove SEO. It expanded it.

References and resource links

SERP features and CTR research

Semrush — SERP features guide
https://www.semrush.com/blog/serp/
Semrush (2025) — AI Overviews study
https://www.semrush.com/blog/semrush-ai-overviews-study/
arXiv (2023) — Beyond Rankings (SERP features and CTR)
https://arxiv.org/abs/2306.01785

Publisher impact and media coverage

Reuters Institute — Digital News Report
https://www.digitalnewsreport.org/
The Guardian (2025) — AI Overviews and traffic
https://www.theguardian.com/media/2025/jul/24/google-ai-overviews
Fortune (2025) — AI search and traffic impact
https://fortune.com/2025/07/24/google-ai-overviews-cut-traffic/
Business Insider (2025) — AI search impact on creators
https://www.businessinsider.com/google-ai-search-creators-traffic-impact

Measurement and monitoring tools

Google Search Console — Performance report
https://support.google.com/webmasters/answer/7576553
Semrush Sensor
https://www.semrush.com/sensor/
Advanced Web Ranking — CTR study
https://www.advancedwebranking.com/ctr-study/

Additional foundational SEO documentation (to round out the library)

Google Search Central — How Search Works
https://developers.google.com/search/docs/fundamentals/how-search-works
Google Search Central — Search Essentials
https://developers.google.com/search/docs/essentials
Google Search Central — Core Web Vitals
https://developers.google.com/search/docs/appearance/core-web-vitals
web.dev — Learn Core Web Vitals
https://web.dev/explore/learn-core-web-vitals
web.dev — Web Vitals overview
https://web.dev/articles/vitals
Google Search Central — Sitemaps
https://developers.google.com/search/docs/crawling-indexing/sitemaps/build-sitemap
Sitemaps protocol
https://www.sitemaps.org/protocol.html
Google Search Central — robots.txt intro
https://developers.google.com/search/docs/crawling-indexing/robots/intro
Google Search Central — robots meta tag
https://developers.google.com/search/docs/crawling-indexing/robots-meta-tag
Google — robots.txt spec
https://developers.google.com/crawling/docs/robots-txt/robots-txt-spec
Google Search Central — canonicalization
https://developers.google.com/search/docs/crawling-indexing/canonicalization
Google Search Central — consolidate duplicate URLs
https://developers.google.com/search/docs/crawling-indexing/consolidate-duplicate-urls
Google Search Central — structured data intro
https://developers.google.com/search/docs/appearance/structured-data/intro-structured-data
Google Search Central — structured data policies
https://developers.google.com/search/docs/appearance/structured-data/sd-policies
Google Search Central — FAQ structured data
https://developers.google.com/search/docs/appearance/structured-data/faqpage
Schema.org — FAQPage
https://schema.org/FAQPage
Schema.org — Article
https://schema.org/Article
Schema.org — Organization
https://schema.org/Organization
Schema.org — Person
https://schema.org/Person
Schema.org — Getting started
https://schema.org/docs/gs.html
Bing — Webmaster Guidelines
https://www.bing.com/webmasters/help/webmaster-guidelines-30fba23a
Microsoft — How Bing delivers results (incl. generative context)
https://support.microsoft.com/en-us/topic/how-bing-delivers-search-results-d18fc815-ac37-4723-bc67-9229ce3eb6a3
IndexNow — documentation
https://www.indexnow.org/documentation
llms.txt proposal
https://llmstxt.org/

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AI SEO or SEO for AI