Are You Experiencing a Decline in Organic Traffic? You’re Not Alone

For years, organic traffic has been the golden KPI, the metric marketers obsessively tracked, the one that reassured us our carefully crafted SEO strategies were working. But the digital landscape is shifting, and the culprit isn’t your keyword strategy, your content team, or even your competitors. It’s artificial intelligence.

As AI-powered search tools start to become more popular, they’re quietly reshaping the way people discover and consume information online. SEMrush even predicts that AI-driven search will fully replace traditional search engines by 2028. That may sound like science fiction, but the early signals are already here, and they’re showing up in your analytics dashboards.

What does this mean for marketers? The playbook we’ve been running for over a decade is being rewritten in real time. Traffic dips are no longer just seasonal fluctuations or the result of algorithm updates, they’re the ripple effects of a fundamental shift in how people find and consume information. And that brings us to the big question: if organic traffic is declining everywhere, what’s really happening under the hood?

The Impact of AI on Organic Traffic

At the heart of this shift is Google’s effort to transform from a search engine into an “answer engine.” AI Overviews, launched in 2024 as part of Google’s Search Generative Experience (SGE), now appear on roughly 13% of queries—more than double from January to March 2025. These summaries leverage machine learning to compile concise, context-aware answers drawn from across the web, often satisfying user intent without the need to click any link. 

Other features like featured snippets, knowledge panels, People Also Ask boxes, and local packs also contribute to the zero‑click dynamic, with nearly 60% of all search queries now ending without a single click.

Some industries have reported organic traffic declines as steep as 15 to 64 percent since AI Overviews were rolled out. 

For marketers who’ve spent years optimizing for long-tail keywords, chasing backlinks, and crafting blog posts to lure visitors, this shift can feel discouraging. But it’s important to remember that it’s not that your efforts are going unnoticed, it’s simply that the playing field has changed.  

Less Traffic, Higher Intent

At first glance, this sounds like a doomsday scenario for SEO. Fewer clicks mean fewer visitors, which means fewer opportunities to engage, nurture, and convert. But here’s the twist: while overall traffic is down, the visitors who do arrive on your site are more intentional than ever.

Casual browsers who might have clicked your link just to skim the answer are being filtered out by AI-generated summaries. The people still coming through are the ones who want more than a quick definition. They’re seeking deeper insights, detailed resources, or product-specific information. And when they land on your site, they’re more primed to take action.

In fact, one study found that visitors driven by large language models (LLMs) are about 4.4 times more likely to convert compared to traditional search visitors. Adobe’s analysis of retail site data during the 2024 holiday season also revealed that visitors coming via AI-driven search stayed 8% longer, visited 12% more pages, and bounced 23% less than those from traditional searches.

So yes, your volume of traffic may be lower, but the quality of leads has the potential to skyrocket.

It’s a tradeoff worth paying attention to. Chasing vanity metrics like sheer visitor numbers might no longer make sense. Instead, success will be measured by how well you capture and serve this smaller but far more valuable audience.

How to Adapt to the Future of AI-Powered Commerce

The landscape may be shifting, but marketers are nothing if not adaptable. This isn’t the end of SEO, it’s just the next evolution of it, so you don’t need to completely rewrite the playbook. Instead, here’s how you can start to rethink your approach and adapt it to the new future of commerce.

1. Start by understanding how these LLMs interpret and talk about your product

The first step in adapting is to understand how LLMs actually process and interpret data. These systems don’t “read” content like a human would; instead, they analyze enormous datasets (product descriptions, technical specifications, schema markup, contextual signals from across the web, etc.) to decide how to surface information. That means accuracy, structure, and consistency matter more than ever. If your product data is incomplete, inconsistent, or overly generic, it’s less likely to be picked up and reflected in AI-generated answers. Optimizing for LLMs is about ensuring your content is machine-readable, semantically clear, and rich enough to stand out in a generative response.

This is where tools purpose-built for the new AI-driven search landscape can make a difference, like Akeneo’s AI Discovery Optimization feature, which helps businesses enrich and structure their product information in ways that align with how LLMs interpret data. By bridging the gap between human-friendly product storytelling and machine-friendly precision, our tool increases the likelihood that your products will be correctly understood, represented, and recommended in AI-powered search experiences. In short, it equips you not just to adapt to the shift but to thrive in it.

2. Incorporate measuring referral traffic from LLMs into your KPIs

The next step is to rethink the way you measure success. Large language models often act as intermediaries, surfacing and contextualizing your content within their own responses before a user ever clicks through. That means valuable touchpoints with your brand are happening outside the walls of your website, and if you’re only looking at conventional web analytics, you’re missing a big part of the picture. 

Start by broadening your reporting to include traffic from AI-powered discovery channels: conversational search tools, generative platforms, and embedded assistants inside apps. These sources may not look like classic referral traffic, but they’re increasingly where high-intent buyers begin their journey.

Tracking this kind of engagement is about recognizing the quality and behavior of the visitors arriving through these new pathways. Segment your analytics to compare how AI-driven referrals perform against traditional organic search: Are they spending more time on site? Are they converting at higher rates? Over time, this will help you identify the true economic value of AI referrals and adjust your strategy accordingly. By aligning KPIs with this new reality, you’ll be better positioned to understand where your most valuable customers are coming from and how to serve them effectively, even as the search landscape continues to evolve.

3. Focus on delivering original, thought leadership content over keyword-driven overviews

The era of casting a wide net with dozens of keyword-targeted posts is fading fast. AI-powered search doesn’t reward sheer volume, it rewards clarity, authority, and depth. Large language models are trained to synthesize content, and when faced with a sprawling collection of surface-level articles, they’ll often bypass them in favor of sources that go deep into a subject. That means your content strategy should shift from trying to capture every possible keyword variation to building comprehensive, authoritative resources that showcase your expertise. A well-researched guide or in-depth explainer will not only perform better with AI-driven search but also resonate more with the high-intent visitors who do land on your site.

This shift also changes the way we think about content planning. Instead of aiming for dozens of quick-turn blog posts, focus on cornerstone content pieces that can serve as definitive resources on key topics relevant to your audience. These pieces can then be supported by complementary assets like case studies, product guides, and customer stories that reinforce the same themes and strengthen your authority in the eyes of both human readers and AI systems. In short, less is more, provided “less” means strategically curated, deeply valuable, and optimized for how modern discovery tools evaluate relevance.

4. Treat customer feedback as the valuable ranking signal it is

LLMs don’t just scan your website—they also draw on a wide range of external inputs, from reviews and testimonials to social media discussions and industry forums. In fact, a recent study shows that Reddit, Quora, and LinkedIn were amongst the most cited websites for Google AI Overviews. 

Every authentic mention of your brand helps reinforce its authority, making it more likely that AI-generated answers will reference you as a trusted source. This makes it critical to foster real, verifiable proof points: customer success stories, ratings on third-party platforms, and a steady cadence of mentions in industry conversations.

This also means that social engagement is no longer just a brand-building exercise, but a direct lever for search visibility. Rather than shying away from platforms where conversations may feel less controllable, marketers should lean into them strategically. Encourage customers to share their experiences, amplify positive feedback, and actively participate in discussions where your expertise adds value. When AI models repeatedly encounter your brand in credible, context-rich settings, they “learn” to trust it.

How to Win in the Age of AI

The decline in organic traffic can feel unsettling, especially for teams that have long relied on SEO as their primary growth driver (that is to say, pretty much every team). But the reality is that search is simply changing, not disappearing. AI may be taking over the top of the funnel, but it’s also filtering out casual visitors and leaving you with the kinds of prospects you’ve always wanted: serious, high-intent buyers.

By shifting your mindset and adapting your strategy, you can turn this challenge into an opportunity. Learn how AI interprets your brand, measure new referral paths, focus on content depth, and listen closely to the voice of your customers. The future of search belongs to those who embrace change, not resist it.

So the next time you open your analytics dashboard and see fewer visitors, don’t panic. Remember: fewer doesn’t mean worse. In fact, in the age of AI-powered search, fewer might just mean better.