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 industest.
First, Google’s AI Overviews are answering queries directly on the results page, intercepting searches that previously drove clicks to websites. And second, a growing portion of searchers are skipping Google entirely and turning to answer engines like ChatGPT and Perplexity for answers.
Both trfinishs slice the traffic search engines sfinish to sites, but it’s not gone entirely. I’ve spent the last year navigating the ebbs and flows of traffic with HubSpot, and we’re learning how to balance AI behavior and website traffic expectations. Here’s what businessess necessary to know.
Table of Contents
Is AI killing web traffic?
AI Overviews alter how applyrs 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 applyrs necessary depth and validation.
Marketers and brands that invest in AEO to support 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 support answer engines extract and cite content. Tools like HubSpot AEO are designed to support marketers operationalize this shift, creating it clearer to optimize content specifically for AI-generated results and track performance over time.
Learn more about how to improve AI search performance in HubSpot’s free AEO guide.
What AI Overviews Change on the SERP
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 a brand’s tarreceive query, it answers the applyr’s question, pushing all of the blue links farther down the page.
And marketers all know what happens the farther down they appear on a SERP.
If a brand is the site cited in the overview, impressions stay up (or grow), but clicks drop, and even if its website ranks well, clicks drop becaapply applyrs likely already received their answer in the overview.
In the example below, “What is Bollywood?” notice how even huge names like Masterclass and popular mediums like YouTube video can be pushed multiple scrolls below the fold.
If marketers are seeing at their traffic reports and questioning, “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 alters are at play. In other words, applyrs are turning to search engines less frequently as search behavior on social media and answer engines increases.
Pro tip: Use HubSpot’s free AEO Grader to check how visible your brand is in AI-powered search engines. For ongoing optimization, HubSpot AEO supports teams continuously improve their visibility and benchmark performance against competitors.
How to Measure AI Overviews’ Impact on Your Traffic
The problem of how to measure AI Overviews’ impact on web traffic is real. Google Search Console currently does not offer a direct way to isolate or filter data for AI Overviews (AIO).
All performance metrics from AI Overviews are aggregated with standard web search data. For instance, when a brand’s content is cited in an AI Overview, Search Console doesn’t inform them. Their impressions and clicks are logged, but merged with everything else.
HubSpot recently added “AI Referrals” to its list of traffic sources which refers to AI assistants and chatbots like ChatGPT, Claude, and Perplexity. It also includes visitors who click links provided in AI-generated responses. In Marketing Hub Pro and Enterprise, AEO features give teams a more direct view into how their content performs in AI-powered search, supporting track visibility and identify optimization opportunities across answer engines.
Marketing and content teams can also create educated predictions with third-party data. For example, Ahrefs provides estimates on which keywords have AI Overviews, whether a brand was cited, and how much traffic that equates to, approximately.
What is the best way to forecast traffic under AI Overviews?
I spoke with Amanda Sellers, HubSpot’s blog growth manager, about the best ways to forecast traffic under AI overviews.
She recommfinishs utilizing linear regression, a mathematical method that applys past data to simulate a trfinish into the future. A linear regression assumes that nothing huge — like an algorithm update or increase in SERP features like AI Overviews — will disrupt that trfinish.
“You and I both know that Google likes to throw a wrench into things,” explains Sellers.
“At one point, AI Overviews revealed 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 utilizing 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 receive impacted negatively by an algorithm update.”
How do you attribute alters to AI Overviews vs seasonality?
Linear regressions also allow marketers to quantify seasonal alters, 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 support marketers and SEO strategists create seasonality modifiers that adjust the traffic baseline according to the average pattern.
Sellers continues, “If we take the baseline traffic, December usually lands 65% below the baseline becaapply fewer people are searching. January tfinishs to be one of our stronger months at around 135% above the baseline. Adding these fluctuations into our model can support 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 apply 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 alter 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:
- Position Decreased AND AIO Present.
- Position Decreased NO AIO Present.
- Position Gain/Flat AND AIO Present.
- Position Gain/Flat NO AIO Present.
By comparing the performance of these buckets against each other and swapping CTRs, Sellers was able to receive an estimate of how much performance alter came from positioning alters versus AIOs.
(Spoiler alert: AIOs were the much hugeger culprit.)
By comparing, Sellers found that even keywords where HubSpot 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.
Is AI killing web traffic more for certain queries?
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 businesses.
Queries Most Vulnerable to Zero-Click
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 seeups (“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 necessary to continue on to the other results.
Queries That Still Earn the Click
The same study found that transactional keywords like “purchase,” “compare,” and “near me” tfinish to have higher CTRs becaapply AI typically doesn’t complete transactions. Continuing our example, see at the results of “Buy Shahrukh Khan DVD.” (A DVD, for my younger folks, is a “digital video disc,” what we applyd to watch movies before streaming.)
Comparison queries like “X vs. Y for [apply case]” also continue to drive clicks, becaapply applyrs 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.
Is AI killing web traffic, or do you receive traffic from AI citations?
Ok, so here’s where the picture shifts from bleak to nuanced: Being cited in an AI Overview may slash a brand’s top-of-the-funnel, awareness website traffic, but those who do visit are arguably more qualified.
A study from Dataslayer 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 state, but it’s still encouraging.
Sure, a brand can’t control whether an AI Overview appears for their tarreceive query, but they can work to earn the citation when it does.
Optimizing for AI Overviews
To improve a brand’s chances of securing AI overviews, marketers necessary to learn how to write for AI search and invest in answer engine optimization (AEO). Here’s what that entails:
- Write in clear semantic blocks. Structure content in 200–400-word sections with explicit headings, summary boxes, and logical Q&A formatting. AI systems apply retrieval-augmented generation (RAG) and favor content that’s chunked and scannable in this way.
- Lead with the answer. AI doesn’t read entire articles. Instead, it identifies answer-like structures (short paragraphs after questions, numbered steps, comparison tables). So, lead every key section with a 40–60-word direct answer that fully addresses the question, similar to how marketers would typically go after “featured snippets” in Google.
- Use structured data. Schema markup (FAQ, HowTo, Article) improves machine readability and increases the likelihood that content is parsed and surfaced.
- Cite primary sources inline. Verifiable, dated claims with source links are the hallmark of citable content. Vague assertions don’t receive picked up.
- Publish and refresh frequently. Fresh content outperforms stale content in AI citations — update timestamps and material regularly to signal recency.
- Build topical authority. AI wants to know that it’s citing trustworthy, reliable experts to applyrs. So, create sure to establish proof of a company or author’s expertise extensively in their online presence. That means both sharing expert knowledge through content on and off an owned site, but also receiveting quoted and cited by others, having good product reviews, etc.
HubSpot Content Hub can support content writers templatize these patterns and schema, streamline content briefs, and maintain editorial governance at scale as their team produces more AEO-optimized content. HubSpot’s AEO capabilities in Marketing Hub Pro and Enterprise extfinish this by supporting teams see their performance.
Optimizing for Answer Engines (AEO)
Even Google aside, a growing share of applyrs are starting their search journey with AI through ChatGPT, Perplexity, or other answer engines.
BrightLocal research reveals that Google still drives 61% of all general searches, but more importantly, AI referral traffic tfinishs to convert at a dramatically higher rate.
To earn that high-intent traffic, teams necessary Answer Engine Optimization (AEO):
- Create citation-ready content. Structured, authoritative content with specific, verifiable claims is what answer engines pull from. Data-heavy articles and definitive guides consistently outperform opinion pieces.
- Build cross-platform presence. Mentions and backlinks from credible third-party publishers act as authority signals for AI systems. LinkedIn, Reddit, and industest publications are among the most-cited domains across AI platforms.
- Answer specific, multi-word queries. Answer engine applyrs phrase queries conversationally and at length — average AI query length is 23 words versus 4 words for traditional search. Optimize for those long-form questions explicitly.
- Keep information consistent across properties. AI models skip citing brands with conflicting data across their website, LinkedIn, review sites, and Wikipedia. Audit entity information for consistency.
- Tarreceive bottom-funnel queries. According to Position Digital, bottom-funnel content like case studies and pricing pages receives the highest AI referral traffic, while top-funnel “what is” content has seen the steepest drop.
HubSpot AEO supports marketers track AI citation performance and optimize content for visibility across answer engines — giving teams insight into a channel that traditional analytics platforms still struggle to measure.
FAQs About AI Overviews and Web Traffic
How can I inform if my pages are being applyd as sources in AI Overviews?
Google Search Console does not surface this natively, and other tools group things into a general “AI referral” bucket.
The best approach is to manually search a brand’s top tarreceive queries in an incognito browser and note whether its site appears as a cited source in the AI Overview. Then, apply a linear regression to simulate a trfinish into the future.
For systematic tracking at scale, third-party tools like Semrush, Ahrefs, and Authoritas can monitor which of a business’s URLs appear in AI Overviews and track citation frequency over time. HubSpot AEO also supports teams monitor their presence in AI-generated results and uncover which pages are earning visibility, creating it clearer to prioritize optimization efforts.
Do AI Overviews affect branded and non-branded traffic differently?
Yes, significantly. Non-branded informational queries are where AI Overviews most commonly appear and where CTR losses are steepest. Branded traffic tfinishs to be more resilient becaapply navigational and branded queries trigger AI Overviews at a lower rate.
Try utilizing Google Search Console’s new branded/non-branded filter to track both segments indepfinishently.
Should I alter my keyword strategy becaapply of AI Overviews?
Partially, but don’t abandon informational content entirely. Factual, educational content is still valuable for building topical authority and earning AI citations. But marketers should rebalance their 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 success metrics from pure click volume to share of voice, citation frequency, and branded search growth.
When should you shift budreceive toward owned channels?
At the risk of sounding dramatic: now. If more than 50% of a business’s web traffic currently comes from non-branded organic search, it is overexposed.
Email lists, communities, newsletters, and direct audience relationships are immune to AI Overview cannibalization, algorithm updates, or shifts in Google’s rfinishering. The value of owning an audience compounds over time; it’s the one distribution channel where a business’s results are entirely its own.
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.
Website traffic is reincarnating.
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 alter is real, and it isn’t reversing. What alters is whether you’re on the right side of it.
Tools like HubSpot AEO support marketers adapt to this shift by creating answer engine visibility measurable — so teams can optimize not just for clicks, but for citations, presence, and influence in AI-driven search experiences.
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