The published estimates range from about 5% to about 58%, and the range is not noise. It tracks study design almost perfectly: the weaker the identification, the larger the number.
The two studies with genuine causal designs are also the two nobody quotes, because their findings are less alarming and they were not published by companies that sell search software. Meanwhile the platform itself has responded with adjectives.
This page sorts every available estimate by how it was produced, and says what actually determines your own exposure.
The two studies that can support a causal claim
Both are recent, neither is peer reviewed, and both are far better identified than anything else available.
The randomized experiment. Over 1,000 US participants recruited through a research panel, each installing a purpose-built browser extension, randomly assigned to a control group, a group with summaries hidden, or a group redirected to the conversational mode. Data collected 7 January to 10 February 2026, two weeks of observation per participant.
What it found, verbatim. That the appearance of a summary reduced users’ organic clicks to third-party sites by 39.8 percent and increased searches where the user clicked on no links at all by 34.5 percent. Citations within summaries generated relatively little referral traffic, about 8% of all clicks.
Why the design matters. Random assignment removes the query-type confound by construction. Whether you saw a summary was decided by the experiment, not by what you searched for.
The natural experiment. A difference-in-differences analysis using online encyclopedia clickstream data from December 2023 to December 2024, exploiting the staggered geographic rollout together with the multilingual structure of the encyclopedia. Two matched samples: 499,927 English-German article pairs and 530,873 English-French pairs.
What it found, verbatim. That default summary availability reduced English search traffic by 5.45% and 4.82% respectively, which the authors translate to roughly 100.27 million fewer search-originated visits per month.
Why that design is also strong. The same article in another language serves as its own control, which holds content and query type constant.
And why the two disagree. The authors of the second study address this directly, noting their effect is considerably smaller and attributing the gap to the panel’s nature and the opt-in design of the experiment. They also describe their own estimate as a reduced-form effect of the default regime rather than the effect conditional on a summary actually appearing, which would attenuate it.
The range tracks identification strength. The two studies that can support causation report the smaller effects. Source : Published studies, opened directly (2026)
What people actually did, on a real panel
Between the experiments and the tool studies sits one observational study of genuine navigation, and its numbers are the most concrete available.
The sample.900 US adults on a panel that records real browsing through an installed application. 68,879 unique Google searches captured, of which 12,593 triggered an AI summary. Browsing observed through March 2025, with results pages scraped in April 2025 to identify retrospectively which queries had produced a summary.
The headline comparison. Users clicked a traditional link on 8% of visits where a summary appeared, against 15% where none did.
Clicks on sources inside the summary.1% of visits.
Session endings.26% of pages with a summary ended the session, against 16% without.
What it establishes. That in real navigation, the presence of a summary is associated with roughly half the link-clicking. That is a substantial, well-measured association.
What it does not establish. Causation. The queries that trigger summaries are not a random subset, and the study makes no causal claim.
Why the 1% matters more than it looks. The common reassurance is that citations inside summaries send traffic instead. On this panel they sent almost none, and the randomized experiment reached a compatible conclusion, putting citation traffic at about 8% of all clicks.
Not because anyone is lying. Because of a structural problem the design cannot escape.
The confound.99.2% of keywords that trigger a summary are informational. Comparing queries that have summaries against queries that do not is therefore also comparing informational queries against everything else, and those have different click rates regardless of any AI feature.
What the better tool study does about it. Restricts both sides to informational keywords, which removes part of the problem. It still compares different queries rather than the same query before and after.
What the France study does about it. Names the issue and declines to resolve it. Its authors write that a slope is not a prediction, acknowledge late-July seasonality, and describe the summary rate as a risk factor rather than a cause.
What the client-data study does about it. States it plainly: that it cannot claim causation, and that higher-authority brands are also more likely to be cited.
So the honesty is mostly present. The caveats are in the source documents. They fall off in transmission, which is how a carefully hedged correlation becomes a headline percentage.
And the commercial position matters. Every one of these studies was published by a company selling search software or search consulting. That does not make the data wrong, and their willingness to publish samples and caveats is better than most of the industry. It belongs in the citation.
The platform has responded twice at senior level. Both responses are worth reading closely for what they do not contain.
August 2025, from the head of Search. That overall, total organic click volume from Google Search to websites has been relatively stable year-over-year.
The quality claim, verbatim. That average click quality has increased and that Google is sending slightly more quality clicks to websites than a year ago, defining quality clicks as those where users do not quickly click back.
The attack on the studies. That this data is in contrast to third-party reports which inaccurately suggest dramatic declines in aggregate traffic, often based on flawed methodologies, isolated examples, or traffic changes that occurred prior to the rollout of AI features.
What the post contains in support. No figure. No percentage. No chart. No sample, period or denominator.
July 2026, from a senior vice president. That Google is now sending billions of clicks to websites every week through AI features in Search alone. Again no denominator, which is the number that would make it meaningful.
How to weigh this. Google is the only party that can see the whole picture, and its assertion may well be right. But an assertion criticising others for flawed methodology, while publishing no methodology of its own, cannot settle the question. It is a claim, at the same evidential level as the studies it dismisses, minus the samples.
The global percentage is not your percentage, and the thing that determines yours is knowable from your own data.
The mechanism. Summaries appear overwhelmingly on informational queries. If your organic traffic comes from brand searches and transactional queries, your exposure is small. If it comes from guides, definitions and comparisons, it is large.
Which describes B2B unusually well. B2B organic strategy is built on informational content: what is X, how does Y work, X versus Y. That is precisely the query class where summaries appear.
One tracking vendor’s sector figures. Summary coverage on B2B technology queries rising from 36% to 82% in a year, with health at 72% to 88%, while commerce queries were held far lower.
The caveat on those figures. They come from a proprietary rank-tracking parser rather than observed behaviour, published by a company selling search software. Treat them as an order of magnitude and a direction.
A widely circulated B2B statistic I am not going to repeat. A specific comparison of summary frequency on B2B versus consumer keywords circulates everywhere. I could not trace it to any study with a disclosed sample, so it is not in this article.
The number you can actually compute. Open Search Console, split your organic clicks into brand, informational and transactional, and look at the informational share. That fraction is your exposure. Everything above is context for interpreting it.
Five moves that are correct under any of the published estimates.
Compute your informational share first. Before reacting to a global figure, find out how much of your organic traffic is even in the exposed category.
Stop treating rankings as the outcome. Position is now a weaker proxy for traffic than it was, because the click rate attached to a position has changed. Measure clicks and conversions, not positions.
Judge content on assisted revenue, not sessions. A page that gets summarised and cited may still influence a purchase. If your only measure is sessions, you will delete pages that are working.
Write for the question, not the keyword. Content that answers a specific question with something a summary cannot reproduce, your own data, your own method, a named case, is what earns the click that remains.
And keep the channel in proportion. If organic informational traffic was 15% of your pipeline, a 40% reduction on part of it is a manageable problem. Sizing it before reacting is the whole discipline here.
The published range is 5% to 58%, and it tracks study design: the weaker the identification, the larger the number.
The randomized experiment on 1,000+ participants found a 39.8% reduction in organic clicks and a 34.5% rise in searches with no click at all.
The natural experiment on about a million article pairs found 5.45% and 4.82%, roughly 100 million fewer visits a month.
The behavioural panel of 900 adults found link clicks on 8% of summary visits against 15% without, and 1% clicking a cited source.
Citation traffic is small in both: about 1% on the panel, about 8% of all clicks in the experiment.
99.2% of summary keywords are informational, which is the confound the tool studies cannot fully escape.
Google says traffic is “relatively stable” and click quality has risen, in posts containing no figure, percentage or chart.
None of this is peer reviewed. The two strongest studies are 2026 preprints.
Compute your informational share before you react to anyone’s percentage. Book a diagnostic, or see how we approach B2B websites.
Frequently asked questions
How much organic traffic do AI Overviews actually cost?
It depends entirely which study you read. Commercial SEO tools report up to 58% CTR reduction at position one. The two studies with causal designs report 39.8% and around 5%. Nobody has a peer-reviewed answer.
Which study is the most reliable?
Two are much stronger than the rest by design: a randomized field experiment with over 1,000 participants, and a difference-in-differences analysis using the same encyclopedia article in different languages as its own control.
What did the behavioural panel find?
Across 900 US adults and 68,879 searches, users clicked a traditional link on 8% of visits where a summary appeared, against 15% where none did. Only 1% clicked a source cited inside the summary.
Why do the SEO tool numbers run higher?
Probably because of a structural confound. 99.2% of keywords that trigger a summary are informational, so comparing summary against non-summary queries also compares query types, which have different click rates anyway.
What does Google say?
That total organic click volume has been relatively stable year over year, and that average click quality has increased. Both statements appear in posts containing no figures, no percentages and no charts.
Is any of this peer reviewed?
No. The two strongest studies are a working paper and an arXiv preprint, both from 2026. The rest are published by companies selling SEO software or consulting.
Are B2B sites more exposed than B2C?
Structurally, yes, because B2B organic traffic leans on informational queries and those are where summaries appear. One tracking vendor reports B2B technology coverage rising from 36% to 82% in a year.
What should I actually do about it?
Work out what share of your own organic traffic comes from informational queries rather than brand and transactional ones. That ratio, not anyone's global percentage, determines your exposure.