Is AI Killing Web Traffic? How AI Overviews Impact Organic Website Traffic
Every few years, marketing headlines announce the demise of one foundational strategy or another. First, email; then blogging; then search engines. Now, with the rise of AI comes the question, “Is AI killing web traffic?” — But the curiosity...
Konoly
Every few years, marketing headlines announce the demise of one foundational strategy or another. First, email; then blogging; then search engines. Now, with the rise of AI comes the question, “Is AI killing web traffic?” — But the curiosity is actually warranted. As of December 2025, AI Overviews chop organic click-through rate (CTR) for position-one content by an average of 58%, and that's no coincidence. We’re in the middle of a huge shift in how search engines surface information, and it’s rewriting the rules for marketers and content teams across every industry. One, Google's AI Overviews are answering queries directly on the results page, intercepting searches that previously drove clicks to websites. And two, a growing portion of searchers are skipping Google entirely and turning to AI engines like ChatGPT and Perplexity for answers. Both trends slice the traffic search engines send to your site, but it’s not gone entirely. I've spent the last year navigating the ebbs and flows of traffic with HubSpot, and fine tuning to balance AI behavior and website traffic expectations. Here’s what you need to know. Table of Contents AI Overviews change how users interact with search results by reducing CTR for some informational queries and redistributing clicks rather than eliminating all website traffic. Simple fact-based queries are more likely to trigger zero-click results, while more detailed, branded questions like comparisons are more likely to earn clicks when users need depth and validation. Marketers and brands that invest in AEO to help capture AI overviews rather than ignoring them are the brands that will stay competitive. Original research improves citation potential in AI answers, structured data improves machine-readability of page content, and concise Q&A sections help answer engines extract and cite content. Learn more about how to improve your AI search performance in HubSpot’s free AEO guide. AI Overviews are generated summaries that appear at the top of Google's search results, above both paid ads and organic listings. When one appears for your target query, it answers the user's question, pushing all of the blue links we’re used to seeing farther down the page. And we all know what happens the further you appear down a SERP. If you're the site mentioned in the overview, impressions stay up (or grow), but clicks drop. Even if you rank well, clicks drop because users likely already got their answer in the overview. In my example, “What is Bollywood?” notice how even big names like Masterclass and popular media like YouTube videos can push multiple scrolls below the fold. According to McKinsey, half of Google's results already feature AI-powered features like overviews, and trends predict that number will reach 75% by 2028. And thanks to those features, Google itself reports that over 27% of searches now end without a click. If you’re looking at your traffic reports and asking, “Why did my website traffic drop after ai search?” — this is the “zero-click” reality. A study by Seer Interactive found that organic CTR for AI Overview queries dropped by 61% from June 2024 to September 2025. Even more alarming: the CTR of queries without AI Overviews also fell by 41% in the same period. This suggests broader behavioral changes are at play. In other words, users are turning to search engines less frequently as search behavior on social media and AI engines increases. But let’s bring all this big-picture talk back down to earth and what it means for your business. Pro tip: Use HubSpot's free AI Search Grader to check how visible your brand is in AI-powered search engines. This will give you a reliable baseline for seeing where you can improve, along with the rest of the advice we’ll share. The measurement problem is real. Google Search Console currently does not offer a direct way to isolate or filter data for AI Overviews. All performance metrics from AI Overviews are aggregated with standard web search data. For instance, when your content is cited in an AI Overview, Search Console doesn't tell you. Your impressions and clicks are logged, but merged with everything else. HubSpot recently added “AI Referrals” to its list of traffic sources (which is great), but it currently refers only to AI assistants and chatbots like ChatGPT, Claude, and Perplexity. It also includes visitors who click links provided in AI-generated responses. You can, however, make educated predictions with third-party data. For example, Ahrefs provides estimates on which keywords have AI Overviews, whether your brand was cited, and how much traffic that equates to, approximately. I spoke with Amanda Sellers, HubSpot’s blog growth manager, about the best ways to forecast traffic under AI overviews. She recommends using linear regression, a mathematical method that uses past data to simulate a trend into the future. A linear regression assumes that nothing big — like an algorithm update or increase in SERP features like AI Overviews — will disrupt that trend. “You and I both know that Google likes to throw a wrench into things,” explains Sellers. “At one point, AI Overviews showed up for less than 10% of the HubSpot blog’s keywords, most of them being informational definition intent. Today, nearly 50% of the keywords the HubSpot blog ranks for have an AI Overview at the top.” For this reason, Sellers frequently checks AI Overview exposure in Ahrefs and performs CTR curve analysis using data from Google Search Console. That way, multiple scenarios can be forecasted on top of the baseline linear regression, such as “what if AI Overviews increase by 20%” or “what if we get impacted negatively by an algorithm update.” Linear regressions also allow you to quantify seasonal changes, determining patterns in historical data. For example, there might be a historical pattern of low traffic in December compared to November due to holiday seasonality. A linear regression can help marketers and SEO strategists create seasonality modifiers that adjust the traffic baseline according to the average pattern. She continues, “If we take the baseline traffic, December usually lands 65% below the baseline because fewer people are searching. January tends to be one of our stronger months at around 135% above the baseline. Adding these fluctuations into our model can help us understand if there is unexpected performance in one direction or another.” If a traffic forecast already factored in seasonality in this way, any performance anomalies in one way or another would mean seasonality is not the culprit. From there, an SEO strategist can use Ahrefs to determine whether Google increased the visibility of AIOs or whether another factor was at play. However, it’s not always that simple. “Keywords rise and fall, AIOs appear and disappear, algorithm updates come and go… and there are internal technical factors that can impact performance. In reality, attributing performance is so much more complex.” For instance, after a particularly tough algorithm update, Sellers found 46.7% of a subsection of HubSpot’s keywords lost positioning and gained an AI Overview. It’s much more difficult to attribute how much of the performance change was the AI Overview siphoning traffic versus a decrease in CTR from simply a lower SERP position. For this reason, it’s best to let the data speak for itself. Sellers split the keywords into different buckets: By comparing the performance of these buckets against each other and swapping CTRs, Sellers was able to get an estimate of how much performance change came from positioning changes vs. AIOs. (Spoiler alert: AIOs were the much bigger culprit.) By comparing, Sellers found that even keywords where we didn't lose positioning still had significant CTR losses. This means there was less traffic, even when we were performing well. Meanwhile, by swapping CTAs and multiplying by impressions, we could estimate the traffic decline. Not all queries are affected by AI Overviews. Thankfully, the data is becoming clearer about which types feel the greatest zero-click impact and which can still drive website traffic for your business. Queries most vulnerable to zero-click: In 2025, Semrush reported that nearly 95% of keywords triggering AI Overviews have little to no paid ads or commercial value. In other words, Google seems to be deploying AI summaries mainly for informational searches, with transactional content (i.e pricing pages, demo pages) staying in the traditional SERP format. That means the website traffic most at risk is top-of-funnel educational content that typically grabs a lot of clicks for businesses and builds brand awareness. Think simple right-or-wrong lookups (“what is [concept]”, “how to” explainers, definition queries, and single-source informational questions), like this example: “Who is Shahrukh Khan?” This question is answered by Google in an AI overview so there’s less need to continue on to the other results. Queries that still earn the click: The same study found that transactional keywords like “buy,” “compare,” and “near me” tend to have higher CTRs because AI typically doesn't complete transactions. Continuing our example, look at the results of “Buy Shahrukh Khan DVD.” (A DVD for my younger folks is a “digital video disc,” what we used to watch movies before streaming.) Comparison queries like “X vs. Y for [use case]” also continue to drive clicks, because users want depth and validation that a two-paragraph AI summary can't fully provide. The same is true for queries that require local, real-time, or highly specific information. Overall, the best content for generating clicks and website traffic is currently bottom-funnel content (pricing pages, comparison guides, case studies), local service queries, niche technical queries, and original research that AI can't synthesize from elsewhere. Ok, so here's where the picture shifts from bleak to nuanced: being cited in an AI Overview may slash your top-of-the-funnel, awareness website traffic, but those who do visit are arguably more qualified. Recent studies found that brands cited in AI Overviews earn 35% more organic clicks and 91% more paid clicks than brands not cited in the same queries. Whether this is due to greater awareness or other factors is hard to say, but it’s still encouraging. Sure, you can't control whether an AI Overview appears for your target query, but you can work to earn the citation when it does. To improve your chances of securing AI overviews, you need to learn how to write for AI search and invest in answer engine optimization (AEO). Here’s what that entails: HubSpot Content Hub can help you templatize these patterns and schema, streamline content briefs, and maintain editorial governance at scale as your team produces more AEO-optimized content. Even Google aside, a growing share of users are starting their search journey with AI through ChatGPT, Perplexity, or other AI engines. BrightLocal research shows that Google still drives 61% of all general searches, but more importantly, AI referral traffic tends to convert at a dramatically higher rate. To earn that high-intent traffic, you need Generative Engine Optimization (GEO): HubSpot's AEO tools help marketers track AI citation performance and optimize content for visibility across AI Overviews and answer engines — so you can measure the channel that traditional analytics still misses. Google Search Console does not surface this natively and tools like HubSpot group things into a general “AI referral” bucket. Your best approach is to manually search your top target queries in an incognito browser and note whether your site appears as a cited source in the AI Overview. Then, use a linear regression to simulate a trend into the future. For systematic tracking at scale, third-party tools like Semrush, Ahrefs, and Authoritas can monitor which of your URLs appear in AI Overviews and track citation frequency over time. Yes, significantly. non-branded informational queries are where AI Overviews most commonly appear and where CTR losses are steepest. Branded traffic tends to be more resilient because navigational and branded queries trigger AI Overviews at a lower rate. Try using Google Search Console's new branded/non-branded filter to track both segments independently. Partially, but don’t abandon informational content entirely. Factual, educational content is still valuable for building topical authority and earning AI citations. But you should rebalance your investment toward comparison content, bottom-funnel queries, and original research that AI can't fully synthesize. The goal is to be the source AI cites, not to avoid the queries AI covers. Shift your success metrics from pure click volume to share of voice, citation frequency, and branded search growth. At the risk of sounding dramatic, now. If more than 50% of your traffic currently comes from non-branded organic search, you're overexposed. Email lists, communities, newsletters, and direct audience relationships are immune to AI Overview cannibalization, algorithm updates, or shifts in Google‘s rendering. The value of owning your audience compounds over time; it’s the one distribution channel where your results are entirely yours. Publishers with high branded and direct traffic, like the Daily Mail (whose over 60% of traffic is direct) have proven significantly more resilient to AI Overview disruption than sites reliant on non-branded organic search. AI is not killing web traffic — it's redistributing it. Clicks are declining for informational queries, especially non-branded ones. But traffic from AI citations, for the brands that earn it, converts at rates that dwarf traditional organic search. The marketers who win in the battle against AI impact on website traffic are the ones who stop measuring success purely in clicks and start experimenting with measuring visibility, citation frequency, and audience ownership. The structural change is real, and it isn‘t reversing. What changes is whether you’re on the right side of it.
TLDR: Executive Summary
What AI Overviews Change on the SERP
How to Measure AI Overviews' Impact on Your Traffic
What is the best way to forecast traffic under AI Overviews?
How do you attribute changes to AI Overviews vs seasonality?
Is AI Killing Web Traffic More for Certain Queries?
Is AI Killing Web Traffic, or Do You Get Traffic from AI Citations?
Optimizing for AI Overviews
Optimizing for Generative AI Engines (GEO)
FAQs About AI Overviews and Web Traffic
How can I tell if my pages are being used as sources in AI Overviews?
Do AI Overviews affect branded and non-branded traffic differently?
Should I change my keyword strategy because of AI Overviews?
When should you shift budget toward owned channels?
Website Traffic is Reincarnating
