Yoast announced the addition of llms.txt capability to both the premium and free versions of their SEO plugin. Users can now add llms.txt files to their sites to future-proof them for AI search engines.
LLMS.Txt
llms.txt is a proposal for a new standard that will enable large language models (LLMs) to access a publisher’s content in a way that is easy for LLMs. The main content is presented to LLMs without advertising and other page elements that target humans.
The proposed standard uses markdown in pages with the .md file name, duplicates of existing pages that only contain the main content. Google’s John Mueller has alluded to the inherently untrustworthiness of the proposed standard because there’s nothing to stop unscrupulous SEOs from adding whatever they want to the LLMs.txt web pages.
It simply makes more sense to just grab the content from the normal web pages. Additionally, LLMs aren’t currently looking for those pages and it’s quite likely that they will continue to use the normal web pages.
Yoast’s announcement states:
“Helps AI tools understand your site better: Guides large language models like ChatGPT and Gemini to your most relevant content.
Highlights your key content automatically: No need to decide what to include. Yoast SEO detects your most important and recently updated pages.
No technical setup required: The file is generated and refreshed weekly, no coding or manual work needed.
Future-proof your website for AI search: Make sure your site is ready for how people find information today, and tomorrow.
Built into Yoast SEO, free for everyone: Available in one click, no upgrade needed.”
This post was sponsored by MarketBrew. The opinions expressed in this article are the sponsor’s own.
Is Google using AI to censor thousands of independent websites?
Wondering why your traffic has suddenly dropped, even though you’re doing SEO properly?
Between letters to the FTC describing a systematic dismantling of the open web by Google to SEO professionals who may be unaware that their strategies no longer make an impact, these changes represent a definite re-architecting of the web’s entire incentive structure.
While some were warning about AI passage retrieval and vector scoring, the industry largely stuck to legacy thinking. SEOs continued to focus on E-E-A-T, backlinks, and content refresh cycles, assuming that if they simply improved quality, recovery would come.
But the rules had changed.
Google’s Silent Pivot: From Keywords to Embedding Vectors
In late 2023 and early 2024, Google began rolling out what it now refers to as AI Mode.
What Is Google’s AI Mode?
AI Mode breaks content into passages, embeds those passages into a multi-dimensional vector space, and compares them directly to queries using cosine similarity.
In this new model, relevance is determined geometrically rather than lexically. Instead of ranking entire pages, Google evaluates individual passages. The most relevant passages are then surfaced in a ChatGPT-like interface, often without any need for users to click through to the source.
Beneath this visible change is a deeper shift: content scoring has become embedding-first.
What Are Embedding Vectors?
Embedding vectors are mathematical representations of meaning. When Google processes a passage of content, it converts that passage into a vector, a list of numbers that captures the semantic context of the text. These vectors exist in a multi-dimensional space where the distance between vectors reflects how similar the meanings are.
Instead of relying on exact keywords or matching phrases, Google compares the embedding vector of a search query to the embedding vectors of individual passages. This allows it to identify relevance based on deeper context, implied meaning, and overall intent.
Traditional SEO practices like keyword targeting and topical coverage do not carry the same weight in this system. A passage does not need to use specific words to be considered relevant. What matters is whether its vector lands close to the query vector in this semantic space.
How Are Embedding Vectors Different From Keywords?
Keywords focus on exact matches. Embedding vectors focus on meaning.
Traditional SEO relied on placing target terms throughout a page. But Google’s AI Mode now compares the semantic meaning of a query and a passage using embedding vectors. A passage can rank well even if it doesn’t use the same words, as long as its meaning aligns closely with the query.
This shift has made many SEO strategies outdated. Pages may be well-written and keyword-rich, yet still underperform if their embedded meaning doesn’t match search intent.
What SEO Got Wrong & What Comes Next
The story isn’t just about Google changing the game, it’s also about how the SEO industry failed to notice the rules had already shifted.
Don’t: Misread the Signals
As rankings dropped, many teams assumed they’d been hit by a quality update or core algorithm tweak. They doubled down on familiar tactics: improving E-E-A-T signals, updating titles, and refreshing content. They pruned thin pages, boosted internal links, and ran audits.
But these efforts were based on outdated models. They treated the symptom, visibility loss, not the cause: semantic drift.
Semantic drift happens when your content’s vector no longer aligns with the evolving vector of search intent. It’s invisible to traditional SEO tools because it occurs in latent space, not your HTML.
No amount of backlinks or content tweaks can fix that.
This wasn’t just platform abuse. It was also a strategic oversight.
SEO teams:
Many believed that doing what Google said, improving helpfulness, pruning content, and writing for humans, would be enough.
That promise collapsed under AI scrutiny.
But we’re not powerless.
Don’t: Fall Into The Trap of Compliance
Google told the industry to “focus on helpful content,” and SEOs listened, through a lexical lens. They optimized for tone, readability, and FAQs.
But “helpfulness” was being determined mathematically by whether your vectors aligned with the AI’s interpretation of the query.
Thousands of reworked sites still dropped in visibility. Why? Because while polishing copy, they never asked: Does this content geometrically align with search intent?
Do: Optimize For Data, Not Keywords
The new SEO playbook begins with a simple truth: you are optimizing for math, not words.
The New SEO Playbook: How To Optimize For AI-Powered SERPs
Here’s what we now know:
AI Mode is real and measurable. ✅You can calculate embedding similarity. ✅You can test passages against queries. ✅You can visualize how Google ranks.
Content must align semantically, not just topically. ✅Two pages about “best hiking trails” may be lexically similar, but if one focuses on family hikes and the other on extreme terrain, their vectors diverge.
Authority still matters, but only after similarity. ✅The AI Mode fan-out selects relevant passages first. Authority reranking comes later. ✅If you don’t pass the similarity threshold, your authority won’t matter.
Passage-level optimization is the new frontier. ✅Optimizing entire pages isn’t enough. Each chunk of content must pull semantic weight.
How Do I Track Google AI Mode Data To Improve SERP Visibility?
It depends on your goals; for success in SERPs, you need to focus on tools that not only show you visibility data, but also how to get there.
Profound was one of the first tools to measure whether content appeared inside large language models, essentially offering a visibility check for LLM inclusion. It gave SEOs early signals that AI systems were beginning to treat search results differently, sometimes surfacing pages that never ranked traditionally. Profound made it clear: LLMs were not relying on the same scoring systems that SEOs had spent decades trying to influence.
But Profound stopped short of offering explanations. It told you if your content was chosen, but not why. It didn’t simulate the algorithmic behavior of AI Mode or reveal what changes would lead to better inclusion.
That’s where simulation-based platforms came in.
Market Brew approached the challenge differently. Instead of auditing what was visible inside an AI system, they reconstructed the inner logic of those systems, building search engine models that mirrored Google’s evolution toward embeddings and vector-based scoring. These platforms didn’t just observe the effects of AI Mode, they recreated its mechanisms.
As early as 2023, Market Brew had already implemented:
Passage segmentation that divides page content into consistent ~700-character blocks.
Embedding generation using Sentence-BERT to capture the semantic fingerprint of each passage.
Cosine similarity calculations to simulate how queries match specific blocks of content, not just the page as a whole.
Thematic clustering algorithms, like Top Cluster Similarity, to determine which groupings of passages best aligned with a search intent.
This meant users could test a set of prompts against their content and watch the algorithm think, block by block, similarity score by score.
Where Profound offered visibility, Market Brew offered agency.
Instead of asking “Did I show up in an AI overview?”, simulation tools helped SEOs ask, “Why didn’t I?” and more importantly, “What can I change to improve my chances?”
By visualizing AI Mode behavior before Google ever acknowledged it publicly, these platforms gave early adopters a critical edge. The SEOs using them didn’t wait for traffic to drop before acting, they were already optimizing for vector alignment and semantic coverage long before most of the industry knew it mattered.
And in an era where rankings hinge on how well your embeddings match a user’s intent, that head start has made all the difference.
Visualize AI Mode Coverage. For Free.
SEO didn’t die. It transformed, from art into applied geometry.
To help SEOs adapt to this AI-driven landscape, Market Brew has just announced the AI Mode Visualizer, a free tool that simulates how Google’s AI Overviews evaluate your content:
Enter a page URL.
Input up to 10 search prompts or generate them automatically from a single master query using LLM-style prompt expansion.
See a cosine similarity matrix showing how each content chunk (700 characters) for your page aligns with each intent.
Click any score to view exactly which passage matched, and why.
Answer engine optimization is not new. Google has answered queries directly in search results since 2014 when it launched featured snippets, and a year later with “People also ask.”
Now, with the rise of ChatGPT, Gemini, Claude, Perplexity, and other generative AI platforms, optimizing content to appear as sources or citations is crucial.
Here’s how.
Research questions
Start with understanding the questions of your target audience.
Monitor dialogue and feedback. Keep an eye on Reddit and similar social sites for discussions of your products and company. Track direct customer support queries. Whatever shoppers share on social media and with internal support is likely what they ask on search engines and genAI.
Journeys, not keywords
Don’t try to answer all the questions you’ve identified. Respond instead to specific problems.
Gemini can reveal questions tailored to clear-cut needs. Upload a CSV keyword file and prompt:
List questions that people searching for these keywords may find helpful.
For example, I uploaded a list of keywords for vacationing in Fort Myers, Florida. Gemini suggested highly relevant questions of likely travelers to that locale currently.
What is the current status of hurricane rebuilds in Fort Myers Beach?
How many restaurants, shops, and attractions have reopened?
What areas are best for tourists?
What construction projects, if any, might affect my stay?
Those could be the exact questions of would-be vacationers.
Answer clearly, concisely
Generative AI platforms source clear, well-structured (“chunked”) answers from Q&A formats. To optimize your on-page content:
Ask a question
Immediately follow with a sentence-long answer that’s clear, factual, and easy to understand.
Create separate Q&A sections (or takeaways and conclusions) that help both humans and AI bots.
Multiple studies and experiments have shown that large language models respond to Q&A formats. A recent study intentionally provided contradictory answers to a single question. The LLM selected the correct answer (on a relevant website) when it immediately followed the query.
Use FAQ Schema
AI platforms rely heavily on structured data markup, such as from Schema.org, which helps understand web pages and their content. Free online tools can generate FAQPage schema.
Keywords that contain recipe intent are triggering Google AI Overviews; however, keyword phrases that expressly ask for recipes are triggering the normal recipe rich results. SEOs on social media are reporting that recipe-related queries are triggering AI Overviews, so it may very well be that these are now officially rolled out.
Tom Critchlow (LinkedIn profile) posted about it on LinkedIn. He wasn’t the only one spotting it, there are scattered posts in private Facebook SEO groups that are discussing these as well.
“Starting to see AI Overviews show up for recipe queries and…. I think these are pretty good? Validates my hypothesis that each link will come with a reason to click it…. Recommendations over rankings…”
Is AI Overviews Showing Up For Recipe Queries?
At this time, for me, AI Overviews is not showing up for recipe queries that use the word “recipe” on either desktop or mobile devices. Queries that use the keyword “recipe” or “recipes” still show the regular recipe rich results regardless of device used.
However, queries that have a recipe intent but don’t contain the “recipe” keyword variants do trigger recipe queries.
Recipe Intent Screenshot
Keyword phrases that contain the word “recipe” trigger the normal recipe rich results.
Recipe Keyword Phrase
Keyword phrases that are about recipes but aren’t specifically requesting a recipe tend to trigger AI Overviews. So it’s not really showing AI Overviews for recipe queries, just for queries that are about food and have a latent recipe intent.
Not Showing Up In Mobile Search
The keyword phrases that trigger recipe AI Overviews on desktop do not appear to trigger them on mobile devices. For example, the query Cordon Bleu triggers AIO on the desktop but won’t trigger it on a mobile device.
Keyword Phrase On Mobile Device
The keyword phrase Tom Critchlow shared (healthy dinner ideas) that triggered an AI Overviews on desktop fails to do the same thing on a mobile device.
Mobile Device Results For Query: Healthy Dinner Ideas
So it could be that recipe intent queries have rolled out to desktop users but not yet to mobile devices.
Reduced Traffic To Recipe Bloggers
Recipe bloggers may begin to see reduced levels of traffic from desktop devices. This trend may accelerate as more people begin to rely on chatbots like ChatGPT and Claude for recipes.
ChatGPT Shows Recipes For Recipe Queries
Chatbots are trained to output plausible responses so users may not be able to tell the difference between an authentic recipe and an authentic-sounding recipe. Speaking from personal experience using chatbots for recipes, I find them to be unreliable sources for authentic recipes but that’s probably something that the average home cook won’t notice because the synthetic recipes generally satisfy expectations.
Google’s CEO, Sundar Pichai, responded to concerns about the impact of recent changes in Search and was repeatedly asked to clarify his position on the web ecosystem and how it fits into what he calls the next chapter of search. Pichai’s responses were given in the context of a recent interview on the Lex Fridman podcast.
Google CEO’s Commitment To Web Ecosystem Challenged
Lex Fridman challenged Pichai on whether Google will continue sending users to the human-created web. Pichai responded that supporting the web ecosystem is something he feels deeply about.
Fridman said:
“And the idea that AI mode will still take you to the web, to the human-created web?”
Pichai responded:
“Yes, that’s going to be a core design principle for us.”
Fridman followed up by noting that he’s been asking more questions from Google’s AI Overviews and AI Mode and exploring but he still wants to end up on the “human-created web.”
Pichai responded:
“It helps us deliver higher quality referrals, right? You know where people are like they have a much higher likelihood of finding what they’re looking for. They’re exploring. They’re curious. Their intent is getting satisfied more… That’s what all our metrics show.”
The interviewer added:
“It makes the humans that create the web nervous. The journalists are getting they’ve already been nervous.”
Sundar Pichai answered:
“Look, I think news and journalism will play an important role, you know, in the future we’re pretty committed to it, right? And so I think making sure that ecosystem… In fact, I think we’ll be able to differentiate ourselves as a company over time because of our commitment there. So it’s something I think you know I definitely value a lot and as we are designing we’ll continue prioritizing approaches.”
AI Is The Next Chapter Of Search?
Pichai mentioned that user metrics of AI search are “encouraging” and referred to it as the “next chapter of search,” underlining that AI Search is an inevitability and is not going away.
Search technologies have consistently been in a steady state of change. The strongest effects were visible in the 2004 Florida update, the 2012 Penguin links update, the 2018 Medic update, and the more recent series of helpful content updates, all of which brought massive changes to search rankings. None of those changes are as ambitious and consequential as what the human-created web is facing with Google’s AI Overviews and AI Mode.
Speaking as someone who has been a part of search marketing for over 25 years, I believe Pichai may be understating the situation by calling it the next chapter in search. It may well be that Google AI Search is an entirely new book.
Search Is Evolving To More Context
Lex Fridman remarked on how Google was legendary for its simple layout and the ten blue links, saying that Google is starting to “mess with that” and that surely there must have been battles within Google about that.
Pichai subtly corrected Fridman’s suggestion that Google was moving away from the ten blue links, which hasn’t been a thing for nearly 15 years by stating that the shift to mobile is the reason why Google shifted away from ten blue links, evolving along with the pace of technological advancements and user’s expectations for answers, not links.
Pichai emphasized that Google remains the “front page of the Internet” as Fridman put it, because of their commitment to making it easier for users to explore the web, only with more context.
Pichai answered:
“Look… in some ways when mobile came… people wanted answers to more questions, so we’re …constantly evolving it. But you’re right, this moment, …that evolution, because underlying technology is becoming much more capable. You can have AI give a lot of context.
But one of our important design goals though, is when you come to Google search. You’re going to get a lot of context. But you’re going to go and find a lot of things out on the web. So that will be true in AI mode. In AI overviews and so on.
But I think to our earlier conversation, we are still giving you access to links, but think of the AI as a layer which is giving you context summary. Maybe in AI mode you can have a dialogue with it back and forth on your journey.
But through it all, you’re kind of learning what’s out there in the world. So those core principles don’t change, but I think AI mode allows us to push… we have our best models there, models which are using search as a deep tool.
Really, for every query you’re asking, fanning out doing multiple searches, assembling that knowledge in a way so you can go and consume what you want to and that’s how we think about it.”
Advertising In AI Mode
Something that isn’t immediately apparent is that Google treats advertising as a form of content that is relevant to users. Advertising is not seen as an intrusion but as something relevant to users within a context of their interests.
Fridman next asked him about advertising in AI Mode. Pichai responded that they are currently focusing on getting the “organic experience” right but he also turned to the concept of context.
Pichai’s response:
“Two things.
Early part of AI mode will obviously focus more on the organic experience to make sure we are getting it right. I think the fundamental value of ads are it enables access to deploy the services to billions of people.
Second is, the reason we’ve always taken ads seriously is we view ads as commercial information, but it’s still information. And so we bring the same quality metrics to it.
I think with AI mode, to our earlier conversation, I think AI itself will help us over time, figure out the best way to do it.
Given we are giving context around everything, I think it will give us more opportunities to also explain, okay, here’s some commercial information. Like today, as a podcaster, you do it at certain spots and you probably figure out what’s best in your podcast.
There are aspects of that, but I think the underlying need of people value commercial information. Businesses are trying to connect to users. All that doesn’t change in an AI moment. But look, we will rethink it.”
Will AI Mode Replace Everything?
Lex Fridman asked if Pichai sees a time where AI Mode will become the interface through which the Internet is filtered, asking if there’s a future where it completely replaces the current combination of AI Overviews and ten blue links.
Pichai answered:
“Our current plan is AI Mode is going to be there as a separate tab for people who really want to experience that, but it’s not yet at the level where our main search pages, but as features work, we’ll keep migrating it to the main page. And so you can view it as a continuum. AI model offer you the bleeding edge experience. But things that work will keep overflowing to AI Overviews in the main experience.”
Takeaways
The questions posed by Lex Fridman echo the fears and negative sentiment felt by many publishers about Google’s evolution to providing answers to queries instead of links to the open web.
Sundar Pichai repeatedly stated that Google intends to keep sending users to the human-created web, explaining that AI provides more context that encourages users to explore topics on the web in greater depth.
Those statements, however, are undermined by Google’s delay in enabling web publishers to accurately track referrals from AI Overviews and AI Mode. This creates the impression that publishers are an afterthought and feeds web publisher skepticism about Google’s commitment to the human-created web. While it’s refreshing to hear Google’s CEO emphatically declare his concern for the web ecosystem, I believe it will take more positive actions from Google to overcome web publishers’ negative outlook on the current state of AI search.
Google has confirmed an ongoing disruption that is preventing some results from appearing in Google Lens, Discover, and Voice Search.
According to the company’s Search Status Dashboard, the incident began on June 12 at 1:00 p.m. Pacific Time. A follow-up entry posted at 1:16 p.m. states:
“There’s an ongoing issue with serving Google Lens, Discover, and Voice Search results that’s affecting some users. We’re working on identifying the root cause. The next update will be within 12 hours.”
At press time, the disruption is still marked as “Incident affecting Serving,” meaning the underlying services remain online but are not consistently delivering results.
Why This Matters
Google Lens, the Discover feed, and Voice Search collectively drive significant traffic to publishers, ecommerce catalogs, and local businesses.
When any of these surfaces go dark or return incomplete results, sites that rely on them can experience abrupt drops in impressions and clicks.
What To Do Next
Check for sudden drops in Discover, image, or voice traffic starting around 1:00 p.m. PT. If you see a temporary decline that matches the time on Google’s dashboard, this is likely due to the outage, not a ranking change.
Share Google’s official dashboard notice with website stakeholders. Mention that there will be another update from Google in 12 hours and explain that performance should return to normal once the service is back up.
When Will Service Be Restored?
Google hasn’t offered an estimated time of full resolution, committing only to provide another status update within 12 hours of the 1:16 p.m. post.
Historically, incidents affecting a limited number of users have been fixed within hours, although larger issues can take longer to resolve.
Until Google publishes its next update, the safest assumption is that Lens, Discover, and Voice Search services will remain unpredictable.
The core web search experience is currently listed as “Available,” so blue-link ranking checks and traditional query troubleshooting can proceed as usual.
Google’s Search Relations team has explained why their SEO advice often sounds vague or comes with conditions, such as “it depends.”
In a recent Search Off the Record podcast, team members Martin Splitt and Gary Illyes shared the challenges that prevent them from providing clear-cut answers.
The discussion was part of what the team referred to as a “more human episode.”
The Googlers acknowledged they sometimes come across as robotic and used this episode to show a more human side.
The Context Problem
Splitt works as Google’s bridge between developers and SEO professionals. He provided an example of how good advice can be distorted when people overlook the broader context.
At a Tech SEO Summit, he presented a slide with a bold statement about JavaScript performance. To prevent confusion, he added a note stating that the slide lacked context and provided a full explanation during the talk.
But even with that, he said the statement still got pulled out and repeated on its own.
“I had a remark on that slide saying there’s context missing here, and then I gave all that context… The problem with me saying that in general is that people will just take that one sentence and ignore everything else I said before or after.”
He clarified that JavaScript plays an important role in many web experiences, like enabling offline support. But that nuance often gets lost when single lines are quoted in isolation.
Why Google Doesn’t Share Slides
This loss of context is one reason why Google teams don’t typically share their presentation slides.
Illyes confirmed that slides on their own can be misleading:
He stated:
“Our slides without context, they are useless.”
The team sees what happens when advice meant for one specific situation gets used everywhere. This can hurt websites that have different needs.
For example, advice that works for a small local business might be wrong for a global company with websites in multiple languages.
The “It Depends” Situation
Both Google reps know the SEO community gets frustrated with “it depends” answers.
Splitt even called it his “pet peeve.” But they explained why they can’t give simple yes-or-no answers.
Splitt noted:
“Someone who is serving a very specific niche with highly regulated content in a single country in a single language might have very different requirements than a multilanguage multinational brand that sells everything to everyone.”
They try to give more complete answers by explaining what factors matter. But this makes their advice longer and more complex.
The Google team also worries about how people use their quotes. Splitt said people often pick one statement while ignoring other important information.
Splitt explained:
“It often makes things tricky because people might cherry pick and might pick one thing you said, take that out of context and use it as an example why people should follow their agenda rather than ours.”
While they know public statements can be quoted freely, both reps feel bad when selective quoting gets out of control.
What This Means
The Google team’s openness about their struggles affirms the experience of many SEO professionals.
Google’s guidance often feels cautious because it needs to account for a wide range of use cases.
Instead of seeking simple answers, focus on the factors that influence Google’s recommendations.
Understanding the “why” behind Google’s advice is more useful than chasing one-size-fits-all solutions.
The new AI Mode is rewriting the rules of search. Are you ready?
Google’s AI-generated answers are starting to dominate the SERPs, pushing traditional results further down the page. If your business relies on organic traffic, you can’t afford to ignore this shift.
Join us on June 25, 2025, for an expert-led webinar sponsored by Conductor. Get actionable strategies from Nick Gallagher, SEO Lead at Conductor, to help you adapt fast and stay ahead of the curve.
Traditional SEO tactics are no longer enough. Understanding how AI Mode works and knowing how to respond could be the difference between steady growth and a sharp drop in traffic.
Don’t let AI Mode catch you off guard.
Register today to secure your spot. Can’t make it live? Sign up anyway, and we’ll send you the full recording.
The new AI Mode tab in Google’s results, currently only active in the U.S., enables users to get an AI-generated answer to their query.
You can ask a detailed question in AI Mode, and Google will provide a summarized answer.
Google AI Mode answer for the question [what are the best ways to grow your calf muscles], providing a detailed summary of exercises and tips (Image Credit: Barry Adams)
The critical process is what Google calls a “query fan-out” technique, where many related queries are performed in the background.
The results from these related queries are collected, summarized, and integrated into the AI-generated response to provide more detail, accuracy, and usefulness.
Having played with AI Mode since its launch, I have to admit it’s pretty good. I get useful answers, often with detailed explanations that give me the information I am looking for. It also means I have less need to click through to cited source websites.
I have to admit that, in many cases, I find myself reluctant to click on a source webpage, even when I want additional information. It’s simpler to ask AI Mode a follow-up question rather than click to a webpage.
Much of the web has become quite challenging to navigate. Clicking on an unknown website for the first time means having to brave a potential gauntlet of cookie-consent forms, email signup pop-ups, app install overlays, autoplay videos, and a barrage of intrusive ads.
The content you came to the page for is frequently hidden behind several barriers-to-entry that the average user will only persist with if they really want to read that content.
And then in many cases, the content isn’t actually there, or is incomplete and not quite what the user was looking for.
AI Mode removes that friction. You get most of the content directly in the AI-generated answer.
You can still click to a webpage, but often it’s easier to simply ask the AI a more specific follow-up question. No need to brave unusable website experiences and risk incomplete content after all.
AI Mode & News
Contrary to AI Overviews, AI Mode will provide summaries for almost any query, including news-specific queries:
AI Mode answer for the [latest news] query (Image Credit: Barry Adams)
Playing with AI Mode, I’ve seen some answers to news-specific queries that don’t even cite news sources, but link only to Wikipedia.
For contrast, the regular Google SERP for the same query features a rich Top Stories box with seven news stories.
With these types of results in AI Mode, the shelf life of news is reduced even further.
Where in search, you can rely on a Top Stories news box to persist for a few days after a major news event, in AI Mode, news sources can be rapidly replaced by Wikipedia links. This further reduces the traffic potential to news publishers.
A Google SERP for [who won roland garros 2025] with a rich Top Stories box vs. the AI Mode answer linking only to Wikipedia (Image Credit: Barry Adams)
There is some uncertainty about AI Mode’s traffic impact. I’ve seen examples of AI Mode answers that provide direct links to webpages in-line with the response, which could help drive clicks.
Google is certainly not done experimenting with AI Mode. We haven’t seen the final product yet, and because it’s an experimental feature that most users aren’t engaged with (see below), there’s not much data on CTR.
As an educated guess, the click-through rate from AI Mode answers to their cited sources is expected to be at least as low, and probably lower, as the CTR from AI Overviews.
This means publishers could potentially see their traffic from Google search decline by 50% or more.
AI Mode User Adoption
The good news is that user adoption of AI Mode appears to be low.
The latest data from Similarweb shows that after an initial growth, usage of the AI Mode tab on Google.com in the U.S. has slightly dipped and now sits at just over 1%.
This makes it about half as popular as the News tab, which is not a particularly popular tab within Google’s search results to begin with.
It could be that Google’s users are satisfied with AI Overviews and don’t need expanded answers in AI Mode, or that Google hasn’t given enough visual emphasis to AI Mode to drive a lot of usage.
I suspect that Google may try to make AI Mode more prominent, with perhaps allowing users to click from an AI Overview into AI Mode (the same way you can click from a Top Stories box to the News tab), or integrate it more prominently into their default SERP.
When user adoption of AI Mode increases, the impact will be keenly felt by publishers. Google’s CEO has reiterated their commitment to sending traffic to the web, but the reality appears to contradict that.
In some of their newest documentation about AI, Google strongly hints at diminished traffic and encourages publishers to “[c]onsider looking at various indicators of conversion on your site, be it sales, signups, a more engaged audience, or information lookups about your business.”.
AI Mode Survival Strategies
Broad adoption of AI Mode, whatever form that may take, can have several impactful consequences for web publishers.
Worst case scenario, most Google search traffic to websites will disappear. If AI Mode becomes the new default Google result, expect to see a collapse of clicks from search results to websites.
Focusing heavily on optimizing for visibility in AI answers will not save your traffic, as the CTR for cited sources is likely to be very low.
In my view, publishers have roughly three strategies for survival:
1. Google Discover
Google’s Discover feed may soften the blow somewhat, especially with the rollout onto desktop Chrome browsers.
Expanded presence of Discover on all devices with a Chrome browser gives more opportunities for publishers to be visible and drive traffic.
However, a reliance on Discover as a traffic source can encourage bad habits. Disregarding Discover’s inherent volatility, the unfortunate truth is that clickbait headlines and cheap churnalism do well in the Discover feed.
Reducing reliance on search in favor of Discover is not a strategy that lends itself well to quality journalism.
There’s a real risk that, in order to survive a search apocalypse, publishers will chase after Discover clicks at any cost. I doubt this will result in a victory for content quality.
2. Traffic & Revenue Diversification
Publishers need to grow traffic and income from more channels than just search. Due to Google’s enormous monopoly in search, diversified traffic acquisition has been a challenge.
Google is the gatekeeper of most of the web’s traffic, so of course we’ve been focused on maximising that channel.
With the risk of a greatly diminished traffic potential from Google search, other channels need to pick up the slack.
We already mentioned Discover and its risks, but there are more opportunities for publishing brands to drive readers and growth.
Paywalls seem inevitable for many publishers. While I’m a fan of freemium models, publishers will have to decide for themselves what kind of subscription model they want to implement.
A key consideration is whether your output is objectively worth paying for. This is a question few publishers can honestly answer, so unbiased external opinions will be required to make the right business decision.
Podcasts have become a cornerstone of many publishers’ audience strategies, and for good reason. They’re easy to produce, and you don’t need that many subscribers to make a podcast economically feasible.
Another content format that can drive meaningful growth is video, especially short-form video that has multiplatform potential (YouTube, TikTok, Instagram, Discover).
Email newsletters are a popular channel, and I suspect this will only grow. The way many journalists have managed to grow loyal audiences on Substack is testament to this channel’s potential.
And while social media hasn’t been a key traffic driver for many years, it can still send significant visitor numbers. Don’t sleep on those Facebook open graph headlines (also valuable for Discover).
3. Direct Brand Visits
The third strategy, and probably the most important one, is to build a strong publishing brand that is actively sought out by your audience.
No matter the features that Google or any other tech intermediary rolls out, when someone wants to visit your website, they will come to you directly. Not even Google’s AI Mode would prevent you from visiting a site you specifically ask for.
A brand search for [daily mail] in Google AI Mode provides a link to the site’s homepage at the top of the response (Image credit: Barry Adams)
Brand strength translates into audience loyalty.
A recognizable publisher will find it easier to convince its readers to install their dedicated app, subscribe to their newsletters, watch their videos, and listen to their podcasts.
A strong brand presence on the web is also, ironically, a cornerstone of AI visibility optimization.
LLMs are, after all, regurgitators of the web’s content, so if your brand is mentioned frequently on the web (i.e., in LLMs’ training data), you are more likely to be cited as a source in LLM-generated answers.
Exactly how to build a strong online publishing brand is the real question. Without going into specifics, I’ll repeat what I’ve said many times before: You need to have something that people are willing to actively seek out.
If you’re just another publisher writing the same news that others are also writing, without anything that makes you unique and worthwhile, you’re going to have a very bad time. The worst thing you can be as a publisher is forgettable.
There is a risk here, too. In an effort to cater to a specific target segment, a publisher could fall victim to “audience capture“: Feeding your audience what they want to hear rather than what’s true. We already see many examples of this, to the detriment of factual journalism.
It’s a dangerous pitfall that even the biggest news brands find difficult to navigate.
Optimizing For AI
In my previous article, I wrote a bit about how to optimize for AI Overviews.
I’ll expand on this in future articles with more tips, both technical and editorial, for optimizing for AI visibility.
