The Impact Of AI Overviews & How Publishers Need To Adapt via @sejournal, @MattGSouthern

Google rolled out AI Overviews to all U.S. users in May 2024. Since then, publishers have reported significant traffic losses, with some seeing click-through rates drop by as much as 89%. The question isn’t whether AI Overviews impact traffic, but how much damage they’re doing to specific content types.

Search (including Google Discover and traditional Google Search) consistently accounts for between 20% and 40% of referral traffic to most major publishers, making it their largest external traffic source. When DMG Media, which owns MailOnline and Metro, reports nearly 90% declines for certain searches, it’s a stark warning for traditional publishing.

After more than a year of AI Overviews (and Search Generative Experience), we have extensive data from publishers, researchers, and industry analysts. This article pulls together findings from multiple studies covering hundreds of thousands of keywords, tens of thousands of user searches, and real-world publisher experiences.

The evidence spans from Pew Research’s 46% average decline to DMG Media’s 89% worst-case scenarios. Educational platforms like Chegg report a 49% decline. But branded searches are actually increasing for some, suggesting there are survival strategies for those who adapt.

This article explains what’s really happening and why, including the types of content that face the biggest changes and which are staying relatively stable. You’ll understand why Google says clicks are “higher quality” even as publishers see traffic declines, and you’ll see what changes might make sense based on real data rather than guesses.

AI Overviews are the biggest change to search since featured snippets were introduced in 2014. They’re affecting the kinds of content publishers produce, and they’re increasing zero-click searches, which now make up 69% of all queries, according to Similarweb.

Whether your business relies on search traffic or you’re just watching industry trends, these patterns are significantly impacting digital marketing.

What we’re seeing is a new era in search and a change that is reshaping how online information is shared and how users interact with it.

AI Overview Studies: The Overwhelming Evidence

Google’s AI Overviews (AIO) have impacted traffic across most verticals and altered search behavior.

The feature, which was first introduced as Search Generative Experience (SGE) announced at Google I/O in May 2023, now appears in over 200 countries and 40 languages following a May 2025 expansion.

Independent research conducted throughout 2024 and 2025 shows click-through rate reductions ranging from 34% to 46% when AI summaries appear on search results pages.

Evidence from a variety of independent studies outlines the impact of AIO and shows a range of effects depending on the type of content and how it’s measured:

Reduced Click Through Rates – Pew Research Center

A study by Pew Research Center provides a rigorous analysis. By tracking 68,000 real search queries, researchers found that users clicked on results 8% of the time when AI summaries appeared, compared to 15% without them. That’s a 46.7% relative reduction.

Pew’s study tracked actual user behavior, rather than relying on estimates or keyword tools, validating publisher concerns.

Google questioned Pew’s methodology, claiming that the analysis period overlapped with algorithm testing unrelated to AI Overviews. However, the decline and its connection to AI Overview presence suggest a notable relationship, even if other factors played a role.

Position One Eroded – Ahrefs

Ahrefs’ analysis found that position one click-through rates dropped for informational keywords triggering AI Overviews.

Ryan Law, Director of Content Marketing at Ahrefs, stated on LinkedIn:

“AI Overviews reduce clicks by 34.5%. Google says being featured in an AI Overview leads to higher click-through rates… Logic disagrees, and now, so does our data.”

Law’s observation gets to the heart of a major contradiction: Google says appearing in AI Overviews helps publishers, but the math of fewer clicks suggests this is just corporate doublespeak to appease content creators.

His post garnered over 8,200 reactions, indicating widespread industry agreement with these findings.

More Zero-Click Searches – Similarweb

According to Similarweb data, zero-click searches increased from 56% to 69% between May 2024 and May 2025. While this captures trends beyond AI Overviews, the timing aligns with the rollout.

Zero-click searches work because they meet user needs. For example, when someone searches for “weather today” or a stock price, getting an instant answer without clicking is helpful. The issue comes when zero-click searches creep into areas where publishers used to offer in-depth content.

Stuart Forrest, global director of SEO digital publishing at Bauer Media, confirms the trend, telling the BBC:

“We’re definitely moving into the era of lower clicks and lower referral traffic for publishers.”

Forrest’s admitting to this new reality shows that the industry as a whole is coming to terms with the end of the golden age of search traffic. Not with a dramatic impact, but with a steady decline in clicks as AI meets users’ needs before they ever leave Google’s ecosystem.

Search Traffic Decline – Digital Content Next

An analysis by Digital Content Next found a 10% overall search traffic decline among member publishers between May and June.

Although modest compared to DMG’s worst-case scenarios, this represents millions of lost visits across major publishers.

AIO Placement Volatility – Authoritas

An Authoritas report finds that AI Overview placements are more volatile than organic ones. Over a two- to three-month period, about 70% of the pages cited in AI Overviews changed, and these changes weren’t linked to traditional organic rankings.

This volatility is why some sites experience sudden traffic drops even when their blue-link rankings seem stable.

Click-Based Economy Collapse For News Publishers – DMG Media

A statement from DMG Media to the UK’s Competition and Markets Authority reveals click-through rates dropped by as much as 89% when AI Overviews appeared for their content.

Although this figure represents a worst-case scenario rather than an average, it highlights the potential for traffic losses for certain search types.

Additionally, there are differences in how AI Overviews affect click-through rates depending on the device type.

The Daily Mail’s desktop CTR dropped from 25.23% to 2.79% when an AI Overview surfaced above a visible link (-89%), with mobile traffic declining by 87%; U.S. figures were similar.

These numbers indicate we’re facing more than just a temporary adjustment period. We’re witnessing a structural collapse of the click-based economy that has supported digital publishing since the early 2000s. With traffic declines approaching 90%, we’ve gone beyond optimization tactics and into existential crisis mode territory.

The submission to regulatory authorities suggests they’re confident in these numbers, despite their magnitude.

Educational Site Disruption – Chegg

Educational platforms are experiencing disruption from AI Overviews.

Learning platform Chegg reported a 49% decline in non-subscriber traffic between January 2024 and January 2025 in company statements accompanying their February antitrust lawsuit.

The decline coincided with AI Overviews answering homework and study questions that previously drove traffic to educational sites. Chegg’s lawsuit alleges that Google used content from educational publishers to train AI systems that now compete directly with those publishers.

Chegg’s case is a warning sign for educational content creators: If AI systems can successfully replace structured learning platforms, what’s the future for smaller publishers?

Reduced Visibility For Top Ranking Sites – Advanced Web Ranking

AI Overviews are dense and tall, impacting the visibility of organic results.

Advanced Web Ranking found that across 8,000 keywords, AI Overviews average around 169 words and include about seven links when expanded.

Once expanded, the first organic result often appears about 1,674px down the page. That’s well below the fold on most screens, reducing visibility for even top-ranked pages.

Branded Searches: The Surprising Exception

While most query types are seeing traffic declines, branded searches show the opposite trend. According to Amsive’s research, branded queries with AI Overviews see an 18% increase in click-through rate.

Several related factors likely contribute to this brand advantage. When AI Overviews mention specific brands, it conveys authority and credibility in ways that generic content can’t replicate.

People seeing their preferred brand in an AI Overview may be more likely to click through to the official site. Additionally, AI Overviews for branded searches often include rich information like store hours, contact details, and direct links, making it easier for users to find what they need.

This pattern has strategic implications as companies that have invested in brand building have a strong defense against AI disruption. The 18% increase in branded terms versus a 34-46% decrease in generic terms (as shown above) creates a performance gap that will likely impact marketing budgets.

The brand advantage extends beyond direct brand searches. Queries combining brand names with product categories show smaller traffic declines than purely generic searches. This suggests that even partial brand recognition provides some protection against AI Overview disruption. Companies with strong brands can leverage this by ensuring their brand appears naturally in relevant conversations and content.

This brand premium creates a two-tier internet, where established brands flourish while smaller content creators struggle financially. The impact on information diversity and market competition is troubling.

Google’s Defense: Stable Traffic, Better Quality

Google maintains a consistent three-part defense of AI Overviews:

• Increased search usage.
• Improved click quality.
• Stable overall traffic.

The company frames AI Overviews as enhancing rather than replacing traditional search, though this narrative faces increasing skepticism from publishers experiencing traffic declines.

The company’s blog post from May, introducing the global expansion, stated:

“AI Overviews is driving over 10% increase in usage of Google for the types of queries that show AI Overviews. This means that once people use AI Overviews, they are coming to do more of these types of queries.”

Although this statistic shows a rise in Google Search engagement, it’s sparked intense debate and skepticism in the search and publishing worlds. Many experts agree that a 10% boost in AI Overview-driven searches could be due to changes in user behavior, but also warn that higher search volumes don’t automatically mean more traffic for content publishers.

A number of LinkedIn industry voices have publicly pushed back on Google’s 10% usage increase narrative. For example, Devansh Parashar writes:

“Google’s claim that AI Overviews have driven 10% more searches masks a troubling trend. Data from independent research firms, such as Pew, show that a majority of users do not click beyond the AI Overview— a figure that suggests Google’s LLM layer is quietly eating the web’s traffic pie.”

Similarly, Trevin Shirey points out concerns about the gap between increased engagement with search queries and the actual traffic publishers see:

“Although Google reports a surge in usage, many publishers are experiencing declines in organic click-through rates. This signals a silent crisis where users get quick answers from AI, but publishers are left behind.”

Google’s claim about increased usage needs to be read carefully. The increase is only for certain types of queries that show AI overviews, not overall search volume.

If users have to make multiple searches to find information they could have gotten in one click, their overall usage might go up, but their satisfaction could actually decrease.

In an August blog post, Google’s head of search, Liz Reid, claimed the volume of clicks from Google search to websites had been “relatively stable” year-over-year.

Reid also asserted that click quality had improved:

“With AI Overviews, people are searching more and asking new questions that are often longer and more complex. In addition, with AI Overviews people are seeing more links on the page than before. More queries and more links mean more opportunities for websites to surface and get clicked.”

A Google spokesperson told the BBC:

“More than any other company, Google prioritises sending traffic to the web, and we continue to send billions of clicks to websites every day.”

Google’s developer documentation states:

“We’ve seen that when people click from search results pages with AI Overviews, these clicks are higher quality (meaning, users are more likely to spend more time on the site).”

Publishers are understandably concerned and question the differences between Google’s description of stability and the actual data showing otherwise.

Jason Kint, CEO of Digital Content Next, notes:

“Since Google rolled out AI Overviews in your search results, median year-over-year referral traffic from Google Search to premium publishers down 10%.”

Kint’s data shatters Google’s carefully crafted image of stability, exposing what many publishers already suspect: The search giant’s promises are increasingly at odds with the realities reflected in their analytics dashboards and revenue reports.

The argument that higher-quality clicks are more valuable doesn’t provide much comfort when revenue is falling short. Even if engagement increases, losing such a large portion of clicks is a serious challenge for many ad-supported businesses.

Echoing these concerns, SEO Lead Jeff Domansky states:

“For publishers, AI Overviews are a direct hit to traffic and revenue models built around clicks and pageviews.”

Although Google claims that AI Overview clicks are of higher quality, many industry experts are skeptical.

Lily Ray, Vice President, SEO Strategy & Research at Amsive, highlights the lack of quality control on Google’s end:

“Since Google’s AI Overviews were launched, I (and many others) have shared dozens of examples of spam, misinformation, and inaccurate, biased, or incomplete results appearing in live AI Overview responses.”

And SEO specialist Barry Adams raises concerns about the quality and sustainability:

“Google’s AI Overviews are terrible at quoting the right sources… There is nothing intelligent about LLMs. They’re advanced word predictors, and using them for any purpose that requires a basis in verifiable facts – like search queries – is fundamentally wrong.”

Adams highlights a philosophical contradiction in AI Overviews: By relying on probabilistic language models to answer factual questions, Google may be misaligning technology with user needs.

This range of voices highlights a growing disconnect between Google’s hopeful engagement claims and the tough realities many publishers are facing as their referral traffic and revenue decrease.

Google hasn’t provided specific metrics defining “higher quality.” Publishers can’t verify these claims without access to comparative engagement data from AI Overview versus traditional search traffic.

Legal Challenges Mount

Publishers are seeking relief through regulatory and legal channels. In July, the Independent Publishers Alliance, tech justice nonprofit Foxglove, and the campaign group Movement for an Open Web filed a complaint with the UK’s Competition and Markets Authority. They claim that Google AI Overviews misuse publisher content, causing harm to newspapers.

The complaint urges the CMA to impose temporary measures that prevent Google from using publisher content in AI-generated responses without compensation.

It’s still unclear whether courts and regulators, which often move at a slow pace, can take action quickly enough to help publishers before market forces make any potential solutions irrelevant. A classic example of regulation trying to keep up with technological advancements.

The rapid growth of AI Overviews suggests that market realities may outstrip legal solutions.

Publisher Adaptations: Beyond Google Dependence

With threats looming, publishers are rushing to cut their reliance on Google. David Higgerson shares Reach’s approach in a statement to the BBC:

“We need to go and find where audiences are elsewhere and build relationships with them there. We’ve got millions of people who receive our alerts on WhatsApp. We’ve built newsletters.”

Instead of creating content for Google discovery, publishers need to develop direct relationships. Email newsletters, mobile apps, and podcast subscriptions provide traffic sources that aren’t affected by AI Overview disruptions.

Stuart Forrest stresses the importance of quality as a key differentiator:

“We need to make sure that it’s us being cited and not our rivals. Things like writing good quality content… it’s amazing the number of publishers that just give up on that.”

However, quality alone may not be enough if users never leave Google’s search results page. Publishers also need to master AI Overview optimization and understand how to make the most of remaining click opportunities.

Higgerson notes:

“Google doesn’t give us a manual on how to do it. We have to run tests and optimise copy in a way that doesn’t damage the primary purpose of the content.”

Another path that’s emerging is content licensing. Following News Corp and The Atlantic partnering with OpenAI, more publishers are exploring direct licensing relationships. These deals typically provide upfront payments and ongoing royalties for content usage in AI training, though terms remain confidential.

What We Don’t Know

There are still many uncertainties. The long-term trajectory of AI Mode, for example, could alter current patterns.

AI Mode

Google’s AI Mode may pose an even bigger threat than AI Overviews. This new interface displays search results in a conversational format instead of 10 blue links. Searchers have a back-and-forth with AI, with occasional reference links thrown in.

For publishers already struggling with AI-powered overviews, AI Mode could wipe out the rest of their traffic.

International Impact

The international effects outside English-language markets remain unmeasured. Since AI Overviews are available in over 200 countries and 40 languages, the impact likely varies by market. Factors like cultural differences in search behavior, language complexity, local competition dynamics, and varying digital literacy levels could lead to vastly different outcomes.

Most current research focuses on English-language markets in developed economies.

Content Creation

The feedback loop between AI Overviews and content creation could reshape what content gets produced and how information flows online.

If publishers stop creating certain types of content due to traffic losses, will AI Overview quality suffer as training data becomes stale?

Looking Ahead: Expanded AI Features

Google intends to continue expanding AI features despite mounting publisher concerns and legal challenges.

The company’s roadmap includes AI Mode international expansion and enhanced interactive features, including voice-activated AI conversations and multi-turn query refinement. Publishers should prepare for continued evolution rather than expecting stability in search traffic patterns.

Regulatory intervention may force greater transparency in the coming months. The Independent Publishers Alliance’s EU complaint requests detailed impact assessments and content usage documentation.

These proceedings could establish precedents affecting how AI systems can use publisher content.

Final Thoughts

The question isn’t whether AI Overviews affect traffic. Evidence overwhelmingly confirms they do. The question is how publishers adapt business models while maintaining sustainable operations.

The web is at a turning point, where the core agreement is being rewritten by the platforms that once promoted the open internet. Publishers who don’t acknowledge this change are jeopardizing their relevance in an AI-driven future.

Those who understand the impact, invest in brand building, and diversify traffic sources will be best positioned for success.

More Resources:

Featured Image: Roman Samborskyi/Shutterstock

When Agents Replace Websites via @sejournal, @DuaneForrester

Let’s talk about an agentic future. As task-completing agents move from concept to adoption, their impact on how we discover and transact online will be significant. Websites won’t vanish, but in many cases, their utility will shrink as agents become the new intermediary layer between people and answers. Domains will still exist, but their value as discovery assets is likely to erode. Building and maintaining a site will increasingly mean structuring it for agents to retrieve from, not just for people to browse, and the idea of domains appreciating as scarce assets will feel less connected to how discovery actually happens.

The growth trajectory for AI agents is already clear in the data. Grand View Research valued the global AI agents market at USD 5.40 billion in 2024, with forecasts reaching USD 50.31 billion by 2030 at an annual growth rate of about 45.8%. Regionally, the Asia-Pacific market was USD 1.30 billion in 2024 and is projected to expand to USD 14.15 billion by 2030, with China alone expected to grow from USD 402.6 million to USD 3.98 billion over the same period. Europe is following a similar path, climbing from USD 1.32 billion in 2024 to USD 11.49 billion by 2030. Longer-term, Precedence Research projects the global agentic AI market will rise from USD 7.55 billion in 2025 to nearly USD 199.05 billion by 2034, a compound growth rate of 43.84%. These forecasts from multiple regions show a consistent global pattern: adoption is accelerating everywhere, and the shift toward agentic systems is not theoretical; it is underway. These figures are about task-completing agents, not casual chat use.

Image Credit: Duane Forrester

Do We Still Need Websites In An Agentic World?

It’s easy to forget how limited the internet felt in the 1990s. On AOL, you didn’t browse the web the way we think of it today. You navigated keywords. One word dropped you into chat rooms, news channels, or branded content. The open web was technically out there, but for most people, America Online WAS the internet.

That closed-garden model eventually gave way to the open web. Domains became navigation anchors. Owning a clean .com or a trusted extension like .org or .gov signaled legitimacy. Websites evolved into the front doors of digital identity, where brand credibility and consumer trust were built. Search rankings reinforced this. An exact-match domain once boosted visibility, and later the concept of “domain authority” helped indicate who showed up at the top of search results. For nearly three decades, websites have been the central hub of digital discovery and transactions.

But we may be circling back. Only this time, the keyword is no longer “AOL Keyword: Pizza Hut.” It’s your natural-language intent: “Book me a flight,” “Order flowers,” “Find me a dentist nearby.” And instead of AOL, the gatekeepers are LLMs and agentic systems.

From Navigation To Answers

The rise of agentic systems collapses the journey we’ve been used to. Where discovery once meant search, scanning results, clicking a domain, and navigating a site, it now means describing your intent and letting the system do the rest. You don’t need Expedia or United.com if your agent confirms your flight. You don’t need to touch OpenTable’s site if a reservation is placed automatically for tomorrow night. You don’t need to sift through Nike’s catalog if new running shoes just arrive at your door.

In this flow, the answer layer replaces the click, the task layer replaces the browsing session, and the source itself becomes invisible. The consumer no longer cares which site delivered the data or handled the transaction, as long as the result is correct.

Proof In Practice: WeChat

This shift isn’t hypothetical. In China, it’s already happening at scale. WeChat introduced Mini-Programs in 2017 as “apps within an app,” designed so users never need to leave the WeChat environment. By 2024, they had become mainstream: Recent reports suggest there are between 3.9 and 4.3 million WeChat Mini-Programs in the ecosystem today. (3.9m source, 4.3m source), with over 900 million monthly active users. And while Mini-Programs are closer to apps than actual AIs, it’s all about task completion and consumers adopting layers of task completion.

In food and beverage and hospitality, over 80% of top chain restaurants now run ordering or take-out flows directly through Mini-Programs, meaning customers never touch a separate website. International brands often prioritize Mini-Programs as their Chinese storefronts instead of building localized websites, since WeChat already handles discovery, product listings, payments, and customer service. Luxury brand LOEWE, for example, launched its 2024 “Crafted World” exhibition in Shanghai entirely via a WeChat Mini-Program, offering ticketing and interactive digital content without requiring users to leave the app.

For many domestic Chinese businesses, this has become the default strategy: their websites exist, if at all, as minimal shells, while the real customer experience lives entirely inside WeChat. And it’s worth keeping in mind, we talked about WeChat serving over 1 billion monthly active users. ChatGPT currently sees over 800 million a week, so roughly three times WeChat’s volume on a monthly basis. An agentic era of direct-to-consumer facilitated by platforms like ChatGPT, WeChat, Claude, Gemini, and CoPilot could bring a massive shift in consumer behavior.

Western Parallels

Western platforms are already moving in this direction. Instagram Checkout allows users to buy products directly inside Instagram, without ever visiting a retailer’s website. Shopify details this integration here. TikTok offers similar flows. Its partnership with Shopify enables in-app checkout so the consumer never leaves TikTok. Even services like Uber now function as APIs inside larger ecosystems. You can book a ride from within another app and never open Uber directly.

In each case, the website still exists, but the consumer may never see it. Discovery, consideration, and conversion all happen inside the closed flow.

The AOL Parallel

The resemblance to the mid-1990s is striking. AOL’s big push came in that period, when its “Keyword” model positioned the service as the internet itself. Instead of typing URLs, people entered AOL Keywords and stayed inside AOL’s curated walls. By mid-1996, AOL had roughly 6 million U.S. subscribers doing this, representing about 13% of the nation’s estimated 44 million internet users at the time.

Today, the “keyword” has become your intent. The agent interprets it, makes the decision, and fulfills the request. The outcome is the same: a closed environment where the gateway controls visibility and access. Only this time, it’s powered by LLMs and APIs instead of dial-up modems.

This is not an isolated evolution. There’s mounting evidence that the open web itself is weakening. Google recently stated in a legal filing that “the open web is already in rapid decline … harming publishers who rely on open-web display advertising revenue.” That report was covered by Search Engine Roundtable.

Pew Research found that when Google displays AI-generated summaries in search results, users click links only 8% of the time, compared to 15% when no summary is present. That’s nearly a 50% decline in link clicks. Digital Content Next reported that premium publishers saw a 10% year-over-year drop in referral traffic from Google during a recent eight-week span.

The Guardian covered MailOnline’s specific case, where desktop click-through dropped 56% when AI summaries appeared, and mobile click-through fell 48%. Advertising spend tells a similar story. MarketingProfs reports that professionally produced news content is projected to receive just 51% of global content ad spend in 2025, down from 72% in 2019. Search Engine Land shows that open-web display ads have fallen from about 40% of Google AdWords impressions in 2019 to only 11% by early 2025.

The story is consistent. Consumers click less, publishers earn less, and advertisers move their budgets elsewhere. The open web will likely no longer be the center of gravity.

If websites lose their central role, what takes their place? Businesses will still need technical infrastructure, but the front door will change. Instead of polished homepages, structured data and APIs will feed agents directly. Verification layers like schema, certifications, and machine-readable credentials will carry more weight than design. Machine-validated authority (how often your brand is retrieved or cited by LLMs) will become a core measure of trust. And partnerships or API integrations will replace traditional SEO in ensuring visibility.

This doesn’t mean websites vanish. They’ll remain important for compliance, long-form storytelling, and niches where users still seek a direct experience. But for mainstream interactions, the website is being demoted to plumbing.

And while design and user experience may lose ground to agentic flows, content itself remains critical. Agents still need to be fed with high-quality text, structured product data, verified facts, and fresh signals of authority. Video will grow in importance as agents surface summaries and clips in conversational answers. First-party user-generated content, especially reviews, will carry more weight as a trust signal. Product data like clean specs, accurate availability, transparent pricing will be non-negotiable inputs to agent systems.

In other words, the work of SEO isn’t disappearing. Technical SEO remains the plumbing that ensures content is discoverable and accessible to machines. Content creation continues to matter, both because it fuels agent responses and because humans still consume it when they step beyond the agent flow. The shift is less about content’s relevance and more about where and how it gets consumed. Web design and UX work, however, will inevitably come under scrutiny as optional costs as the agent interface takes over consumer experiences.

One consequence of this shift is that brands risk losing their direct line to the customer. When an agent books the flight, orders the shoes, or schedules the dentist, the consumer’s loyalty may end up with the agent itself, not the underlying business. Just as Amazon’s marketplace turned many sellers into interchangeable storefronts beneath the Amazon brand, agentic systems may flatten brand differentiation unless companies build distinctive signals that survive mediation. That could mean doubling down on structured trust markers, recognizable product data, or even unique content assets that agents consistently retrieve. Without those, the relationship belongs to the agent, not you.

That potential demotion for websites carries consequences. Domains will still matter for branding, offline campaigns, and human recall, but their value as entry points to discovery is shrinking. The secondary market for “premium” domains is already showing signs of stress. Registries have begun cutting or eliminating premium tiers; .art, for example, recently removed over a million names from its premium list to reprice them downward. Investor commentary also points to weaker demand, with TechStartups noting in 2025 that domain sales are “crashing” as AI and shifting search behaviors reduce the perceived need for expensive keyword names.

We’ve seen this arc before. Families once paid hundreds of dollars for full sets of printed encyclopedias. Owning Britannica on your shelf was a marker of credibility and access to knowledge. Today, those same volumes can be found in thrift stores for pennies, eclipsed by digital access that made the scarcity meaningless. Domains are on a similar path. They will remain useful for identity and branding, but the assumption that a keyword .com will keep appreciating looks more like nostalgia than strategy.

Defensive portfolios across dozens of ccTLDs will be harder to justify, just as stocking encyclopedias became pointless once Wikipedia existed. Websites will remain as infrastructure, but their role as front doors will continue to shrink.

Marketing strategies must adapt. The focus will move from polishing landing pages to ensuring your data is retrievable, your brand is trusted by agents, and your authority is machine-validated. SEO, as we know it, will transform from competing for SERP rankings to competing for retrieval and integration into agent responses.

Another underappreciated consequence of all this is measurement. For decades, marketers have relied on web analytics: page views, bounce rates, conversions. Agentic systems obscure that visibility. If a customer never lands on your site but still books through an agent, you may gain the revenue but lose the data trail. New metrics will be needed. Not just whether a page ranks, but whether your content was retrieved, cited, or trusted inside agent flows. In that sense, the industry will need to redefine what “traffic” and “conversion” even mean when the interface is a conversation rather than a website.

The Fear And The Possibility

The fear is obvious. We’ve been here before with AOL. A closed gateway can dominate visibility, commoditize brands, and reduce consumer choice. The open web and search engines broke us out of that in the late 1990s. No one wants to return to those walls.

But the possibility is also real. Businesses that adapt to agentic discovery (with structured signals, trusted data feeds, and machine-recognized authority) can thrive. The website may become plumbing, but plumbing matters. It carries the flow and information that powers the experience.

So the real question isn’t whether websites will still exist. Ultimately, they will, in some format. The question is whether your business is still focused on decorating the door, or whether you’re investing in the pipes that agents actually use to deliver value.

More Resources:

This post was originally published on Duane Forrester Decodes.

Featured Image: Collagery/Shutterstock

Agentic AI In SEO: AI Agents & The Future Of Content Strategy (Part 3) via @sejournal, @VincentTerrasi

For years, the SEO equation appeared to be a fixed and unchanging landscape: optimizing for Googlebot on one side, and creating content for human users on the other. This outdated binary vision is now a thing of the past.

In the current business environment, a new generation of actors is causing significant changes to the online visibility landscape. AI agents such as ChatGPT, Perplexity, Claude, and Gemini are no longer merely processing information; they are exploring, synthesizing, choosing sources to cite, and significantly influencing traffic flows.

For those who are skeptical about the impact of AI agents, I would invite you to consider the concept of Zero Moment of Truth (ZMOT), which was developed by Google over 10 years ago. The principle is straightforward: Prior to any purchase, consumers undertake an extensive research phase. They consult customer reviews, compare across different sites, scrutinize social networks, accumulate information sources, and now use their favorite AIs for final validation.

A New Paradigm

We are currently experiencing a fundamental reconfiguration of the digital ecosystem. In the past, we have identified two or three main engines. However, a new paradigm is emerging.

Google continues to be a leading search engine, utilizing sophisticated algorithms to index and rank content. Humans act as a virality engine, sharing and amplifying information via their social networks and interactions.

It is becoming increasingly apparent that AI agents are assuming the role of an autonomous traffic engine. These intelligent systems are capable of navigating information independently, establishing their own selection criteria, and directing users to sources they deem relevant.

This transformation necessitates a wholly new approach to content creation, which I will be sharing imminently. I will be sharing concepts and case studies that have been successfully implemented with several major accounts.

Agentic SEO

Quick reminder following my two previous articles on the subject: “Agentic AI In SEO: AI Agents & Workflows For Ideation (Part 1)” and “Agentic AI In SEO: AI Agents & Workflows For Audit (Part 2).”

Agentic SEO involves the creation of structured and dynamic content that is designed to appeal not only to Google, but also to conversational AIs.

The approach to content generation is founded on three key pillars:

1. Data Enrichment: Schema.org data, microformats, and semantic tags are becoming important as, when grounding data, they can facilitate understanding and information extraction by language models.

2. Content Modularity: Concise and “chunkable” responses are perfectly suited to Retrieval-Augmented Generation (RAG) ingestion processes utilized by these agents. Content should be designed using autonomous and reusable blocks.

3. Polymorphism: Each page can offer variants adapted according to the type of agent consulting it. It is essential to recognize that the needs of a shopping agent differ from those of a medical agent, and content must adapt accordingly.

Image from author, September 2025

If your content isn’t optimized for AI agents, you’re already experiencing considerable strategic lag.

However, if your site is optimized for SEO, you’ve already taken a significant step forward.

The Foundations: Generative SEO And Edge SEO

To understand this evolution, it is important to consider the concepts that have prepared the ground: generative SEO and Edge SEO.

Generative SEO

Generative SEO facilitates the creation of substantial and insightful content through the utilization of language models. This approach automates the process of creating content while ensuring its relevance and quality.

Generative SEO has always existed in primitive forms, such as content spinning and all derived techniques. In today’s digital landscape, we are witnessing a paradigm shift towards unparalleled quality, as evidenced by the preponderance of AI-generated or co-written content across various social networks, including LinkedIn.

Edge SEO

Edge SEO leverages CDN or proxy-side deployment capabilities to reduce deployment latency and enable large-scale content testing from both content and performance perspectives.

These two approaches are naturally complementary, but they still represent a 1.0 vision of automated SEO. It is important to note that traditional A/B testing and content freezing, once generation is complete, limit the potential of the project.

The true revolution lies in the adoption of dynamic and adaptive systems that surpass these limitations.

Agentic Edge SEO

Edge SEO had already revolutionized the very notion of static content. The system now has the capability to modify content in real-time according to the following three variables:

• Firstly, user intention is detected and used to guide content adaptation. The system is able to analyze behavioral signals in order to adjust the message in real-time.
• Next, let us consider the impact of SERP seasonality on modifications. When Google prioritizes certain trends on a given query, content automatically adapts to capitalize on these evolutions.
• Finally, the instant technical optimizations triggered by Core Web Vitals signals ensure that performance is maintained.

Image from author, September 2025

Let us consider a product page as a case study. If Google highlights “sustainable” or “economical” trends for a particular search, this page automatically adapts its titles, metadata, and visuals to align with these market signals.

At Draft&Goal, we have developed connectors with the Fasterize tool to facilitate the deployment of AI workflows. These workflows are compatible with all the most recent proprietary or open-source LLMs.

We anticipate that in the future, the system will continuously test these variants with search engines and users, collecting performance data in near real-time.

The most effective version is then selected by the algorithm, in terms of click-through rate (CTR), positioning, and conversion, with results continually being optimized.

For example, imagine a “Running Shoes” landing page, existing in seven distinct versions, each oriented towards a specific angle: price, performance, comfort, ecology, style, durability, or innovation. The polymorphic system automatically highlights the most effective variant according to signals sent by Google and user behaviors.

Three Concrete Applications

These concepts are immediately applicable to several strategic sectors. Allow me to provide three examples of the products currently under active testing.

In ecommerce, product pages are self-evolving. These systems adapt to search trends, available stock, and detected behavioral preferences.

1. To illustrate this point, consider a peer-to-peer car rental platform that manages 20,000 city pages.

Each page automatically adapts according to Google signals and local user patterns. During the summer months, the “Car rental Nice” page automatically prioritizes convertibles and highlights family testimonials. During the winter season, the fleet is transitioned to 4×4 vehicles, with a focus on optimizing the “mountain car rental” service.

2. Another example of technological innovation in the media industry is the ability of major news outlets to deploy “living” articles.

These articles are automatically updated to include the latest breaking news, ensuring that content remains fresh and relevant without the need for human editorial intervention. We continue to prioritize content creation by human professionals, with AI playing a supportive role in maintaining currency.

3. Finally, the promo codes website has successfully managed 3,000 merchant pages, which adapt in real-time to commercial cycles and breaking deals.

Amazon’s Prime Days announcement is met with the automatic enrichment of contextual banners and temporal counters on all related pages. The system is designed to monitor partner APIs in order to detect new offers and instantly generate optimized content. Three weeks before Black Friday, “Zalando promo codes” pages automatically integrate dedicated sections and restructure their keywords.

Toward A New Era Of SEO

The future of SEO lies in publishing dynamic content that can adapt to the ever-changing algorithms of Google’s index. This transformation requires a fundamental paradigm shift, and many SEO agencies we support have already made the switch.

Marketing experts must abandon the “page” logic to adopt that of “adaptive systems.” This transition necessitates the acquisition of new tools and skills, as well as a re-evaluation of our strategic vision.

It is important to note that Agentic SEO is not merely a passing trend; it is the necessary response to an ecosystem undergoing profound mutation. Organizations that master these concepts will gain a significant competitive advantage in tomorrow’s attention economy.

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