Do Google AI Overviews Really Reduce Organic Clicks by 58%?

The Short Answer: 58% Is Real Inside One Model

Yes, for the particular cohort and counterfactual Ahrefs studied. No, as a universal claim that every AI Overview cuts every publisher’s organic traffic by 58%.

The distinction matters because 58% was not the raw fall in click-through rate between two dates. Ahrefs observed a much larger drop in its AI Overview keyword cohort, then used a control cohort to estimate how much of that decline might have happened anyway. The 58% is the remaining gap between the observed December 2025 result and a modeled no-AI-Overview result.

That model answers a useful question: after accounting for the broad decline in click-through rate seen among similar informational searches, how much lower was CTR for keywords that showed an AI Overview? It does not prove that the AI Overview caused the entire difference. The authors explicitly describe the result as a correlation.

Other studies point in the same direction. AI summaries often coincide with fewer clicks to traditional results, but the studies report different magnitudes because they observe different people, queries, positions, brands and outcomes. The strongest reading is therefore not “58% everywhere.” It is that AI Overviews can materially compress organic clicks, especially for informational queries, while the size of the effect depends on the measurement design and whether a page earns a citation.

How Ahrefs Produced the 58% Estimate

Ahrefs’ February 2026 update began with 300,000 keywords divided into two groups. One group contained 150,000 keywords that showed an AI Overview in Ahrefs’ most recent classification. The control group contained 150,000 informational keywords that did not. The analysis used aggregated Google Search Console data for desktop searches and compared December 2023 with December 2025.

For each cohort, Ahrefs calculated click-through rate by dividing total clicks by total impressions. It did not average the CTR of each keyword. That distinction matters because high-impression queries carry more weight in the aggregate.

The control cohort fell from a 7.5730% CTR in December 2023 to 3.8943% in December 2025, a relative decline of about 48.6%. The cohort later labeled as showing AI Overviews fell from 7.2627% to 1.5677%, a raw relative decline of about 78.4%.

If the analysis stopped there, it would be tempting to assign the entire 78.4% decline to AI Overviews. Ahrefs did not do that. It assumed the AIO cohort would have experienced the same proportional decline as the control cohort even without an AI Overview. Applying that control decline to the AIO cohort’s 2023 baseline produced a modeled December 2025 CTR of 3.734%.

The observed CTR was 1.5677%. The gap between 1.5677% and the modeled 3.734% is 58% of the modeled value.

The counterfactual matters

Expressed as estimated clicks per one million impressions, the construction is easier to see. The AIO-labeled cohort produced 72,627 clicks per million impressions at the observed 2023 baseline. Ahrefs’ control-based model projected 37,340 clicks per million in December 2025 without the additional AIO-associated decline. The observed December 2025 result was 15,677, which is 21,663 fewer clicks per million than the model projected.

The middle bar is not a measurement taken from a world without AI Overviews. That world was not observed. It is a counterfactual generated by transferring the control cohort’s proportional decline to the AIO cohort.

This is a standard way to reason about an intervention when a clean experiment is unavailable. Its credibility depends on whether the control cohort represents what would have happened to the treated cohort. If the groups differ in query mix, intent, result layout, seasonality, ranking stability or the tendency to trigger other features, some of the gap may come from those differences.

What 58% does not mean

The figure does not mean every site lost 58% of its Google clicks. The study is concentrated on desktop informational queries and the headline calculation focuses on results ranking first. Ahrefs reported a declining effect lower on the page: 50.8% at position two, 46.4% at position three, 38.8% at position four and 19.4% at position ten.

It also does not mean the same keywords showed AI Overviews throughout the two-year window. Ahrefs grouped keywords by their most recent AIO status and applied that label to earlier Search Console history. That makes the long comparison possible, but it cannot establish the exact date an AI Overview first appeared for every impression.

Finally, 58% is a relative change in CTR, not a percentage-point change and not a direct count of lost visits for a particular site. A page with one million measured impressions at the study’s modeled rate would differ by 21,663 clicks. Most pages have different impression volumes, positions, devices and query mixes.

Other Studies Find Fewer Clicks, but Not One Universal Effect

Ahrefs is not alone in finding click suppression. The more useful question is whether independent designs observe a similar direction after their differences are preserved.

Pew observes user behavior

Pew Research Center measured what 900 U.S. adults actually did during 68,879 Google searches in March 2025. AI summaries appeared on 18% of those searches. When a summary appeared, users clicked a traditional search result on 8% of visits, compared with 15% when no summary appeared. Users clicked a source cited inside the summary on only 1% of visits.

Those are user-level click rates, not Search Console CTR for publishers and not position-one estimates. The comparison nevertheless supports the same directional conclusion: a search page with an AI summary was associated with less outbound clicking. Pew also found that 26% of visits ended after an AI-summary page, compared with 16% on pages without a summary.

The study has its own limits. It observed a U.S. adult browsing panel during one month, and Pew reconstructed search-result pages in April to determine whether the March searches generated summaries. It cannot identify a causal effect for any individual publisher.

Amsive finds smaller averages and larger subgroup effects

Amsive analyzed 10,000 keywords that both produced AI Overviews and already ranked for one of ten client websites across five industries. The agency reported a 15.49% average CTR decline overall. That average concealed sharper differences: nonbranded queries fell 19.98%, results outside the top three fell 27.04%, and queries that combined an AI Overview with a featured snippet fell 37.04%.

Branded queries behaved differently. Only 4.79% triggered an AI Overview in the analyzed set, and their CTR increased 18.68%. The result is a warning against treating one average as a property of the interface itself. Query intent, brand familiarity, result position and competing page features can alter the click path.

Amsive’s client sample is smaller and commercially selected, and its public methodology gives less detail about some comparison choices than the Ahrefs or Pew reports. Its strongest contribution is the subgroup pattern, not a universal effect size.

Seer shows citation status and time can change the headline

Seer Interactive’s April 2026 update examined 5.47 million queries and 2.43 billion organic impressions across 53 brands from January 2025 through February 2026. Its overall AIO-present organic CTR fell to 1.31% in December 2025, then rose to 2.36% by February 2026. Queries without an AIO rose from 3.16% to 3.82% over the same two months.

The rebound does not erase the gap. In February, the AIO-present CTR remained about 38% below the no-AIO rate. But it shows that a point estimate can change quickly as Google changes the product, query coverage shifts, and users adapt.

Citation status also mattered. For informational queries, Seer reported an average organic CTR of 2.07% when the tracked brand was cited, 0.94% when an AIO appeared without citing it, and 3.35% when no AIO appeared. Being cited was associated with a roughly 120% lift over being absent from the citations, while still trailing the no-AIO condition.

Seer applied each query’s most recent AIO label retrospectively and used client data, so the same caution applies: the results are observational and cannot isolate causation. They do, however, show why “AIO present” is too blunt a category for site-level decisions.

The table is not a league table of effect sizes. Its rows observe different levels of the system. Pew counts user clicks after a search page. Ahrefs and Seer use publisher-side Search Console impressions. Amsive focuses on sites that already rank. Google describes total platform traffic. Combining those values into one average would manufacture precision rather than improve it.

Why Google Can Report Stable Total Clicks at the Same Time

In August 2025, Google said total organic click volume from Search to websites had remained relatively stable year over year and that it was sending slightly more “quality clicks,” meaning visits where users were less likely to return immediately to the results page.

The statement appears to conflict with the publisher and user studies. It does not have to.

Google describes the whole platform. A study of informational, desktop, position-one queries describes one slice. Total click volume can remain stable if losses on one class of query are offset by more searches, more clicks on other queries, growth in commercial activity, shifts across devices, or distribution toward different sites. Stable total clicks do not imply stable clicks for every publisher.

The claim also cannot be audited at the same resolution as the independent studies. Google published no numerical time series, sample definition, denominator or reproducible method with the statement. Its definition of a quality click may be useful operationally, but the public evidence does not show how many clicks moved between publishers, query types or result features.

The honest conclusion is that Google’s aggregate claim and the disaggregated studies answer different questions. Neither should be stretched beyond its level of measurement.

What Search Console Can and Cannot Prove

Standard Search Console performance reports include clicks and impressions from links inside AI Overviews in the Web search type. Google counts a click when a user clicks an external link. An impression is counted only when the containing link is scrolled or expanded into view. All links inside one AI Overview inherit the position of that result element.

Those rules let a publisher observe real traffic and exposure. They do not provide a complete historical flag for every query impression that did or did not contain an AI Overview. A conventional export cannot, on its own, separate interface effect from ranking changes, demand changes, query-mix changes or other result features.

In June 2026, Google began a limited rollout of dedicated Search Generative AI performance reports. The launch view lists impressions, pages, countries, devices and dates for generative features, while Google says additional metrics may be added. The dedicated report improves exposure visibility, but its launch fields stop short of a complete click-and-conversion experiment.

Search Console can therefore answer “what happened to this site?” more directly than “what caused it?” Causal attribution requires a design outside the default dashboard.

How to Test the Effect on Your Own Site

A site-level analysis should preserve the query and page conditions that broad studies necessarily average together.

1. Define a stable query-page cohort. Separate brand from nonbrand, informational from commercial intent, desktop from mobile, and top-three results from lower positions.
2. Record AI Overview exposure and citation status on a repeated schedule. A single latest-state label applied to old data is useful for exploration but weak for timing an effect.
3. Track impressions and clicks separately. A click decline caused by fewer impressions is different from a CTR decline at similar exposure.
4. Control for rank and other result features. Featured snippets, shopping units, local packs and changes in title presentation can move CTR independently.
5. Use matched no-AIO queries where possible. Choose queries with comparable intent, demand, rank and seasonality; then inspect whether trends were parallel before the comparison period.
6. Report absolute and relative changes. “Down 50%” means something different when CTR moves from 2% to 1% than when it moves from 20% to 10%.
7. Carry the analysis downstream. Track landing-page engagement, qualified conversions and revenue where consent and attribution permit. A smaller click volume can still contain high-value visits, while an unchanged click total can hide deteriorating quality.

A difference-in-differences model can help when treatment timing and controls are credible, but it should not be treated as an automatic causal stamp. Query features are not randomly assigned, Google changes several systems at once, and AI Overview eligibility itself may correlate with the content and intent that also affect CTR.

Methodology and Limitations

This Data Report synthesizes two Ahrefs studies using aggregated Search Console data, one Pew user-behavior study, two agency analyses, three official Google documentation pages and one official Google traffic statement. The research cutoff is August 21, 2026.

The 58% calculation was independently checked from the values displayed in Ahrefs’ 2026 update. The chart uses the source’s rounded 3.734% counterfactual and converts each CTR to estimated clicks per one million impressions for readability. No cross-study meta-analysis is performed because the sources use incompatible populations, units and comparison designs.

Vendor and agency studies are used as observational evidence, not proof of causation. Google’s official documentation is authoritative for its counting rules, but its traffic statement lacks the public detail required for independent replication. Pew’s panel provides independent behavior evidence but does not estimate publisher-level position effects.

MCP Scraper was used first for source discovery and full-text extraction. The initial discovery batch returned temporary service-unavailable responses; one bounded retry succeeded, after which all nine load-bearing sources were read in full. No search-result snippet supports a material claim.

Conclusion: Treat 58% as a Benchmark, Not a Law

Google AI Overviews can reduce the chance that an impression becomes an organic click. That conclusion is supported by publisher data and independent user-behavior research. The exact 58% figure, however, belongs to Ahrefs’ model: desktop informational keywords, a position-one focus, aggregated Search Console data, a latest-state AIO label, and a control-based counterfactual.

The number is useful because it puts scale on a risk that is easy to dismiss. It is dangerous when stripped of its denominator and turned into a universal forecast.

For publishers, the practical response is not to assume a 58% loss. It is to measure AIO exposure, citation status, position, query intent, impressions and clicks as separate variables; use credible controls; and connect the result to business outcomes. The benchmark says the effect can be large. Your own data must say where it is large, for whom, and whether a citation changes the outcome.

Sources

• “AI Overviews Reduce Clicks by 58%”. Ryan Law, Ahrefs, updated February 4, 2026; vendor study using aggregated Google Search Console data; full text accessed August 21, 2026. Observational and limited to the documented cohort and counterfactual.
• “AI Overviews Reduce Clicks by 34.5%”. Ryan Law, Ahrefs, April 17, 2025; original vendor study; full text accessed August 21, 2026. Superseded for the headline estimate by the 2026 update.
• “AIO Impact on Google CTR: 2026 Update”. Seer Interactive, April 24, 2026; client Search Console analysis; full text. Static latest-state AIO labels and observational client cohort limit causal interpretation.
• “Google users are less likely to click on links when an AI summary appears in the results”. Pew Research Center, July 22, 2025; U.S. adult browsing-panel study; full text. User behavior rather than publisher CTR.
• “Google AI Overviews: New CTR Study Reveals How to Navigate Negative SERP Impact”. Amsive, April 16, 2025; agency client analysis; full text. Commercial sample across ten sites and five industries.
• “AI in Search is driving more queries and higher quality clicks”. Liz Reid, Google, August 6, 2025; official company statement; full text. No reproducible numerical method published.
• “What are impressions, position, and clicks?”. Google Search Console Help; official counting documentation; full text accessed August 21, 2026.
• “AI features and your website”. Google Search Central; official product documentation, updated December 10, 2025; full text.
• “Introducing Search Generative AI performance reports in Search Console”. Hillel Maoz and Moshe Samet, Google Search Central Blog, June 3, 2026; official limited-rollout announcement; full text.