I’ve just discovered that Google is introducing a dynamic new feature within AI Overviews and AI Mode—more visible links that appear as pop-ups when I hover over them on my desktop. These enhanced link cards offer clearer details about the website content.
After testing this feature, Google has now made it live. If you’re curious about what these new pop-up menus look like, here’s a screenshot that showcases them:
Robby Stein from Google recently shared on X: “New on Search: In AI Overviews and AI Mode, groups of links will automatically appear in a pop-up as you hover over them on desktop, so you can jump right into a website to learn more. And we’ll show more descriptive and prominent link icons within the response across both desktop and mobile.”
He also mentioned, “Our testing shows this new UI is more engaging, making it easier to get to great content across the web.”
This update has the potential to drive more traffic to websites, and I personally look forward to seeing increased visitor numbers from Google’s AI enhancements. Although, at the moment, there’s no way to measure its impact in Search Console.
Let me guess: I just spent three months meticulously crafting an optimized product taxonomy, complete with schema markup, internal linking, and standout metadata.
Then, out of nowhere, the product team decided to launch a site redesign without looping me in. Now half of my URLs are broken, the new templates have stripped away my structured data, and my boss is wondering why our organic traffic plummeted by 40%.
Sound familiar?
Here’s the thing: this isn’t an SEO failure, but a governance failure. It’s been costing us countless nights and weekends trying to fix problems that never should have occurred.
This article sheds light on why weak governance keeps breaking SEO, how AI advancements have raised the stakes, and how a visibility governance maturity model can help SEO teams transition from firefighting to prevention.
Governance isn’t bureaucracy – it’s your insurance policy
I know what you’re thinking. “Great, another framework that means more meetings and approval forms.” But hear me out.
The Visibility Governance Maturity Model (VGMM) isn’t about creating red tape. It’s about establishing clear ownership, documented processes, and decision rights that prevent your work from being accidentally destroyed by teams who don’t understand SEO.
Think of it this way: VGMM is the difference between being the person who gets blamed when organic traffic tanks versus being the person who can point to documentation showing exactly where the process broke down – and who approved skipping the SEO review.
This maturity model:
Protects your work from being undone by releases you weren’t consulted on.
Documents your standards so you’re not explaining canonical tags for the 47th time.
Establishes clear ownership so you’re not expected to fix everything across six different teams.
Gets you a seat at the table when decisions affecting SEO are being made.
Makes your expertise visible to leadership in ways they understand.
The real problem: AI just made everything harder
Remember when SEO was mostly about your website and Google? Those were simpler times.
Now I’m trying to optimize for:
AI Overviews that rewrite your content.
ChatGPT citations that may or may not link back.
Perplexity summaries that pull from competitors.
Voice assistants that only cite one source.
Knowledge panels that conflict with your site.
And I’m still dealing with:
Content teams who write AI-generated fluff.
Developers who don’t understand crawl budget.
Product managers who launch features that break structured data.
Marketing directors who want “just one small change” that tanks rankings.
Without governance, I’m the only person who understands how all these pieces fit together.
When something breaks, everyone expects me to fix it – usually yesterday. When traffic is up, it’s because marketing ran a great campaign. When it’s down, it’s my fault.
I become the hero the organization depends on, which sounds great until I realize I can never take a real vacation, and I’m working 60-hour weeks.
What VGMM actually measures – in terms you care about
VGMM doesn’t care about your keyword rankings or whether you have perfect schema markup. It evaluates whether your organization is set up to sustain SEO performance without burning you out. Below are the five maturity levels that translate to your daily reality:
Level 1: Unmanaged (your current nightmare)
Nobody knows who’s responsible for SEO decisions.
Changes happen without SEO review.
You discover problems after they’ve tanked traffic.
You’re constantly firefighting.
Documentation doesn’t exist or is ignored.
Level 2: Aware (slightly better)
Leadership admits SEO matters.
Some standards exist but aren’t enforced.
You have allies but no authority.
Improvements happen but get reversed next quarter.
You’re still the only one who really gets it.
Level 3: Defined (getting somewhere)
SEO ownership is documented.
Standards exist, and some teams follow them.
You’re consulted before major changes.
QA checkpoints include SEO review.
You’re working normal hours most weeks.
Level 4: Integrated (the dream)
SEO is built into release workflows.
Automated checks catch problems before they ship.
Cross-functional teams share accountability.
You can actually take a vacation without a disaster.
Your expertise is respected and resourced.
Level 5: Sustained (unicorn territory)
SEO survives leadership changes.
Governance adapts to new AI surfaces automatically.
Problems are caught before they impact traffic.
You’re doing strategic work, not firefighting.
The organization values prevention over reaction.
Most organizations sit at Level 1 or 2. That’s not your fault – it’s a structural problem that VGMM helps diagnose and fix.
VGMM coordinates multiple domain-specific maturity models. Imagine it as a health checkup that evaluates all your vital signs, not just one metric.
It evaluates maturity across domains like:
SEO governance: Your core competency.
Content governance: Are writers following standards?
Performance governance: Is the site actually fast?
Accessibility governance: Is the site inclusive?
Workflow governance: Do processes exist and work?
Each domain gets scored independently, then VGMM looks at how they work together. Because excellent SEO maturity doesn’t matter if the performance team deploys code that breaks the site every Tuesday or if the content team publishes AI-generated nonsense that tanks your E-E-A-T signals.
VGMM produces a 0–100% score based on:
Domain scores: How mature is each area?
Weighting: Which domains matter most for your business?
Dependencies: Are weaknesses in one area breaking strengths in another?
Coherence: Do decision rights and accountability actually align?
The final score isn’t about effort – it’s about whether governance actually works.
Most importantly, VGMM translates your expertise into language that leadership understands. It protects your work from accidental destruction, so you can focus on strategic, creative, growth-focused work that truly matters.
I’ve noticed a significant shift in how Google Ads operates. No longer is it about simply targeting keywords. Now, it’s all about understanding and leveraging user intent. Here’s what this evolution means for eligibility, structure, and PPC strategy.
Most PPC teams, myself included, have operated on autopilot: compiling keyword lists, assigning match types, and structuring ad groups around search terms. This was the norm.
However, Google’s auction process has transformed. Search interactions are evolving into more conversational experiences. People engage with AI as if they’re having a dialogue, asking follow-up questions and refining their inquiries. AI now reasons through a question before linking it to suitable ads.
Today, the auction isn’t kicked off by a keyword but by the user’s implied intent. If I’m still relying on exact and phrase match structures, I’m planning for a system that’s no longer there. It’s time to embrace intent as the foundation—not the specific words typed, but the underlying goals they signify.
With this intent-first approach, I find a more resilient strategy. It allows me to effectively design campaigns, creativity, and metrics, especially as Google rolls out new AI-focused formats.
While keywords still play a role, they no longer serve as the framework.
Recently, I’ve learned about changes happening under the hood during a search.
Google’s AI now utilizes a method called “query fan out,” which breaks down complex queries into subtopics and conducts simultaneous searches to provide a comprehensive response.
The auction begins even before users finish typing. Importantly, AI can deduce commercial intent from purely informational searches.
For example, if someone asks, “Why is my pool green?” Google understands they’re troubleshooting, not shopping, but identifies potential product needs and displays ads for pool-cleaning supplies. The AI’s reasoning layer recognizes the solution products offer.
This change in auction logic focuses on matching offerings to the user’s inferred intent, rather than merely matching keywords to queries. Recognizing this shift is crucial, or I risk misinterpreting the user journey.
I’ve come to appreciate the intricacies of an intent-first approach. It doesn’t eliminate the need for keyword research but changes how I prioritize keywords. Now, I align campaigns to the user’s intent.
This strategy encourages me to consider:
What problem is the user addressing?
What stage of decision-making are they in?
What role does the product play in solving their issue?
Realizing that the same intent can emerge from various queries and that identical queries can express different intents based on context has been illuminating. Phrases like “Best CRM” might indicate a need for feature comparison or a readiness to purchase; Google’s AI can now make those distinctions, and so should my campaigns.
This shift is more mental than tactical. While I still build keyword lists, they’re now organized by intent rather than match type. My ad copy speaks directly to user goals instead of echoing search terms.
Moving from keywords to intent isn’t merely a tactical alteration—it’s a strategic lens through which I plan for future campaigns, especially as Google enhances its AI-driven ad formats.
Reorganizing campaigns around intent rather than keywords has its immediate effects, impacting eligibility and landing page efficacy while fundamentally influencing system learning.
Google Search is currently experiencing what I see as an ‘expansionary moment,’ powered by the dynamics of AI technology. The search experience I rely on has transformed through longer queries, follow-up questions, and the increasing use of voice and images. This was highlighted during Alphabet’s recent earnings call, where executives shared these evolving trends.
In other words: Google’s search interface is becoming increasingly AI-driven, facilitating interactions within its system. This isn’t about replacing old queries—instead, we’re witnessing a new era of digital exploration.
Why we care. The integration of AI into Google Search is not just a trial. For me, it’s a structural transformation altering how we discover, interact with, and navigate the web.
By the numbers: Alphabet’s Q4 advertising revenue reached $82.284 billion, marking a 13.5% increase from $72.461 billion in 2024.
Google Search & other: $63.073 billion (up 16.7%)
YouTube: $11.383 billion (up 8.7%)
Google Network: $7.828 billion (down 1.5%)
For the 2025 fiscal year, Alphabet’s advertising revenue climbed to $294.691 billion, a growth of 11.4% from the previous year.
Google Search & other: $224.532 billion (up 13.4%)
YouTube: $40.367 billion (up 11.7%)
Google Network: $29.792 billion (down 1.9%)
AI Overviews and AI Mode are now core to Search. Sundar Pichai, Alphabet/Google’s CEO, emphasized how central AI has become to Google’s search products, with over 250 AI-related product launches in just the last quarter.
Google has recently upgraded its AI Overviews to the Gemini 3 model, a move that connects AI Overviews more seamlessly with conversational search experiences.
“We have also made the search experience more cohesive, ensuring the transition from an AI overview to a conversation in AI mode is completely seamless,” Pichai noted.
AI is driving more Google Search usage. As Google puts it, AI-driven search is expanding the ways people use search rather than replacing traditional searches.
“Search saw more usage in Q4 than ever before, as AI continues to drive an expansionary moment,” Pichai emphasized.
“Once people start using these new experiences, they use them more,” he added.
Changing search behavior. AI Mode is making searches longer, more conversational, and multimodal. “Queries in AI mode are three times longer than traditional searches,” said Pichai.
Not only are queries longer, but sessions are also becoming more conversational, often leading to follow-up questions.
“We are also seeing sessions become more conversational, with a significant portion of queries in AI Mode now leading to a follow-up question,” he said.
“Nearly one in six AI mode queries are now non-text, using voice or images,” Pichai shared.
Google’s visual search capabilities continue expanding with “Circle to Search” available on over 580 million Android devices.
“We haven’t seen any evidence of cannibalization,” Pichai said about the coexistence of Google Search and the Gemini app.
“The combination of all of that, I think, creates an expansionary moment,” he concluded.
I recently delved into fascinating research that sheds light on how higher education data informs SEO visibility and AI search. This exploration reveals what truly enhances visibility in this AI-driven era.
Contrary to some beliefs, AI search hasn’t rendered SEO obsolete. Now, the challenge is to excel both in ranking and in earning those vital AI citations.
Every time I Google something these days, there’s a significant chance an AI Overview will appear before any organic results or ads, framing my query, shortlisting sources, and shaping which brands I consider.
According to Ahrefs, AI Overviews now feature for about 21% of keywords. This means that while search rankings remain crucial, AI summaries increasingly dictate early brand consideration.
I’ve noticed that brands aren’t losing visibility just because they slip from the third to the seventh position on search engines. They’re often losing because they’re not even mentioned in AI answers.
Research conducted by Search Influence and UPCEA, where I serve as CEO, reveals insights into AI-assisted search usage and organizational adaptation in the higher education space.
Key Takeaways
AI citations are emerging as a trust signal: Being cited by AI can enhance credibility and secure early user consideration before direct source comparison occurs.
AI visibility is collective: AI pulls from various sources like YouTube, LinkedIn, and beyond—your URL isn’t everything.
Established brands need to adapt: Even well-known brands can be overlooked if their content doesn’t align with how users ask questions.
Most organizations recognize AI’s importance but lack action plans: Awareness exists, but execution is hindered by a lack of ownership and processes.
Content structure determines inclusion: Content that is structured for easy retrieval and decision-making often gets cited over long narratives.
To grasp the evolving search landscape, we need to examine both user behavior and organizational responses.
The findings show increased AI-assisted discovery and shifts in trust signals. Meanwhile, a UPCEA member institution poll uncovers gaps in AI strategy adoption.
The question isn’t whether AI search will impact your field; it’s whether your brand will be cited, overlooked, or represented by competitors.
When it comes to navigating the world of AI search, I’ve found that understanding AEO costs and pricing models can make a big difference in gaining visibility across platforms like ChatGPT, AI Overviews, and answer engines. This budget planner is designed to break down those costs and guide you on where to invest wisely.
As I delve into the specifics of AEO, I’m learning how crucial it is to take into account different pricing models. They don’t just affect the budget but also influence where and how resources should be spent to optimize search outcomes.
I’m excited to explore the strategies that enhance visibility in AI-powered platforms. This process not only boosts my understanding but also equips me with the necessary tools to allocate my budget more effectively, ensuring my efforts in AI search yield the best results.
I’ve come to realize that SEO now serves as both a brand and performance channel. The traditional traffic model has been disrupted by AI Overviews and zero-click SERPs, making brand strength crucial for SEO ROI.
For years, SEO was straightforward: rank higher, get more traffic, then boost the sales pipeline. However, this simple equation is rapidly evolving, much to the frustration of marketing leaders.
With AI Overviews and users getting answers directly from LLMs, the idea of “rank and receive traffic and leads” is less effective now. Even top keyword positions don’t guarantee the clicks they once did.
This shift has sparked challenging discussions in boardrooms. Executives often question, “If traffic is down, how can we measure SEO success?”
It’s obvious now: the traffic model has changed, yet the demand for ROI remains. We must treat SEO as a brand-dependent performance channel, not just a traffic provider.
Why traffic and pipeline are no longer in lockstep
Linear attribution has never fully reflected the dynamic nature of organic search. While ChatGPT isn’t replacing Google, it’s augmenting it.
Users now verify information across platforms due to skepticism of search and LLM results. Where research once happened solely within Google’s ecosystem, it has become more scattered.
Today’s organic search is akin to a pinball machine, with buyers bouncing across channels unpredictably. This introduces complexity that traditional attribution software struggles to follow.
Such complexity has broken the linearity executives crave. Traffic and pipeline charts, once aligned, now often diverge.
Across B2B SaaS portfolios, a common pattern emerges: organic sessions may be flat or declining, yet rankings for high-intent terms stay stable, and the pipeline from organic search grows.
This mismatch doesn’t indicate SEO failure. Rather, it shows that traffic is no longer a reliable business impact measure.
The traffic lost to zero-click searches often consists of informational, low-intent content. What remains is higher-intent traffic, closer to conversion.
We’re seeing the “atomization” of search demand. Short-head, broad keywords are declining, while specific, long-tail queries with higher intent are rising.
Many leaders mistakenly react to dropping sessions by pushing for quantity, aiming to regain the lost numbers through top-of-funnel content. This often inflates vanity metrics without delivering qualified leads.
SEO ROI is now the downstream outcome of brand traction
For years, SEO was viewed as a pure performance channel. We believed optimizing some keywords would suffice.
In reality, SEO has always depended on brand strength. The rise of AI-driven engines highlights this, expecting reputations, not just keywords.
If your brand lacks authority, technical optimizations alone won’t elevate your status. Brand strength determines organic performance limits. Search engines seek web-wide consensus, and weak associations hinder results.
Brand strength for LLMs means owning topical authority, aligning with customer queries, being validated by trusted sources, and having clear positioning.
SEO captures pre-existing demand validated by your brand, not creating it from nothing.
The new defensibility metrics for SEO
As traffic no longer headlines KPIs, new defensibility metrics are necessary. Successful teams focus on revenue and reputation impact, not just volume.
Metrics proving business impact include stable top-10 rankings for commercial keywords, increased Ahrefs traffic value, stable solution page traffic, growing homepage traffic, and developing LLM referral traffic.
When pipeline per organic visitor rises, even with falling sessions, the dialogue shifts from “SEO is broken” to recognizing SEO’s evolution.
Modern SEO is moving from acquisition to influence
Successful SEO isn’t about recovering traffic but influencing buyer decisions and enhancing organic visibility. In an AI-first context, zero-click doesn’t imply zero-value.
SEO remains key in building market readiness, positioning brands as authorities even before buyers enter the funnel.
I recently discovered that Google is considering ways to allow websites to opt out of its AI-generated search features, such as AI Mode and AI Overviews. Naturally, I was curious about how the SEO community felt about it, so I conducted a poll on X to see if site owners would actually opt out.
The results were intriguing. Out of over 350 respondents, the majority mentioned they wouldn’t opt out. However, around one-third indicated they would prefer to block or opt out of these features. Here’s how the responses broke down:
Question: Would you block Google from using your content for AI Overviews and AI Mode?
33.2% – Yes, I’d block Google
41.9% – No, I wouldn’t block
24.9% – I am not sure yet.
Here’s the actual poll for reference:
Would you block Google from using your content for AI Overviews and AI Mode – Google may be giving us more controls – take my poll below. https://t.co/60M3Vt0YlN
But how do you opt out? Right now, that remains a mystery. Google has only mentioned it is exploring possibilities, without providing a clear mechanism. Frankly, the ease or difficulty of opting out could significantly influence decisions. If it’s straightforward, more sites might choose to opt out; if not, fewer will do so.
So why does this matter? We won’t truly know how many sites will opt out until Google officially offers a way to do so. Rest assured, once they do, there will be extensive reporting on the number of sites that decide to opt out.
To give you an idea, The Press Gazette recently reported that around 79% of nearly 100 top news websites in the UK and US are already blocking at least one AI training crawler, including OpenAI’s GPTBot, ClaudeBot, and others.
My advice is simple: Once Google makes this opt-out feature available, give it a test. See firsthand what the impact of opting in or out could be.
I recently came across some intriguing news that Google might soon allow us to prevent our content from being used in their AI search features. Imagine having the power to opt out of AI Overviews and AI Mode!
Google is looking at ways to enable site owners to stop Google from using site content for Search AI’s generative features, like AI Mode and AI Overviews. They’re doing this in response to new guidelines from the UK’s Competition and Markets Authority (CMA). However, Google wants to ensure any new tools don’t disrupt the core functionality of Google Search.
“We’re now exploring updates to our controls to let sites specifically opt out of Search generative AI features.”
They clearly state that these options shouldn’t compromise Google Search, saying:
“Any new controls need to avoid breaking Search in a way that leads to a fragmented or confusing experience for people.”
Anticipated Timeline. It’s uncertain when these new controls will be introduced, but the idea of having more control excites many of us! Many of us—publishers, content creators, site owners—desire control over whether Google can use our content for AI features such as AI Overviews and AI Mode. These forthcoming controls, whenever they appear, will afford us the ability to better manage how Google utilizes our content.
Full Insights. Here’s the full message from Google’s blog this morning:
User behavior is evolving rapidly, and features like AI Overviews help people discover new content and explore more topics. Today, the UK’s Competition and Markets Authority (CMA) initiated a consultation on potential new requirements for Google Search, including the controls we offer websites to manage their content in Search AI features. This matter is complex, as it impacts how people find information and how websites get discovered in Search.
We’ve long provided publishers with a variety of controls, based on standards like robots.txt, to dictate how their content appears in Search. As tech evolves, so do our tools. We’ve added controls for Featured Snippets and image previews (relevant to AI Overviews). Recently, we unveiled Google-Extended, a new tool allowing sites to dictate how their content helps train our Gemini models.
Building on this framework and working alongside the web ecosystem, we’re exploring updates to our controls that specifically allow sites to opt out of Search generative AI features. Our mission is to protect Search’s helpfulness while giving websites the right tools to manage their content. We anticipate engaging in the CMA’s process and continuing our discussions with stakeholders.
New controls need to prevent fragmentation or confusion in Search. As AI becomes central to information discovery, new controls must remain simple and scalable for website owners.
We remain hopeful that we can provide more choice to content creators while ensuring a top-tier and innovative Search experience for users.
Why This Matters. It’s clear that more control is better than less. SEOs, publishers, and site owners have long called on Google to provide controls over how our content is used in AI features. These anticipated controls could arrive soon, so stay tuned for updates!
When I dive into Google Search and opt for a follow-up query, I’m seamlessly transitioned into AI Mode, ensuring my experience flows effortlessly into a conversational format. As Robby Stein, Google Search’s VP of Product, noted, this shift enhances the natural progression of our search interactions.
Globally, these AI Overviews are now powered by Gemini 3 by default, which suggests a significant enhancement in the quality of responses.
Experience the Transition to AI Mode. I remember reading about when Google started testing this transformative feature last December, and it officially confirmed the early tests in October 2025. Now, when I ask a follow-up question, I’m immediately engaged in a conversation directly in AI Mode.
Google emphasizes this transition to a conversation as more user-friendly and seamless within the Google Search experience.
But why this change? During testing phases, it became evident that users, like myself, appreciated a search experience that naturally transitioned into a conversation while maintaining context from AI Overviews, thereby making the search process more helpful.
Here’s a glimpse of how it operates:
When I hit “Show more,” AI Mode elegantly overlays the search results. I have the option to return to the original search with a simple click on the X at the screen’s top right corner. Interestingly, all source citations are stripped from this view, presenting challenges for traffic redirection to content creators.
Gemini 3 Powers AI Overviews. Google has expanded the reach of Gemini 3, making it the standard model for all AI Overviews around the globe. Robby’s message was clear: we’re integrating Gemini 3 to deliver premier AI responses directly on the search results page, especially when it proves beneficial.
This represents a shift from a recent announcement where Gemini 3 Pro was dedicated to managing complex queries in English for specific Google AI subscriptions.
Now, with Gemini 3 as the go-to model for AI Overviews worldwide, I’m curious about its global impact.
Why It Matters to Me. While Gemini 3 promises enhanced responses for AI Overviews, the pivotal change is the redirection of follow-up inquiries into AI Mode from Google Search’s AI Overviews. This shift indicates a potential decrease in clicks leading from Google Search to publisher sites, nudging searchers like me directly into AI Mode.
AI Overviews frequently feature prominently in search results, making it challenging to capture clicks from those citations. With this new follow-up experience, it seems my journey from search to source might get even more streamlined towards AI Mode rather than content creators’ sites.
