I’m watching a new Google Search ad test that could change how people understand sponsored results. Google appears to be experimenting with AI-generated summaries beneath paid search ads, giving its own AI more influence over how advertiser messaging is framed.
What’s happening. Some advertisers are seeing AI-generated summaries appear directly below Google Ads descriptions in Search results. These summaries include a warning from Google that says: “Google AI responses are generated independently and can make mistakes, so double-check responses.”
I first saw this test surface through digital marketer Darcy Burk, who shared a screenshot of the experience on X. The placement is notable because the AI-generated text appears close enough to the ad that users may treat it as part of the paid result, even though Google says the response is generated independently.
Why I care. If Google expands this more broadly, these summaries could shape how users interpret ads by emphasizing the details Google considers most relevant, not necessarily the exact message the advertiser intended to highlight. That raises real questions about accuracy, brand control, and whether click-through rates could be helped or hurt by AI-written context.
Between the lines. Google has already tested AI-generated summaries for organic search listings, so seeing similar functionality move into paid ads feels like another step in bringing generative AI deeper into the Search experience. What I still do not know is how these summaries are created, what sources they rely on, or whether advertisers will get any say in the copy.
What I’m watching. Google has not publicly announced this feature or responded to requests for comment, so it is unclear whether this is a small experiment or the beginning of a wider rollout. Until Google explains the mechanics, advertisers are left guessing how much control they may have over AI-generated text attached to their ads.
The bottom line. Google is testing AI-generated summaries inside Search ads, and I see that as a sign that generative AI could soon play a larger role in paid search presentation, even when advertisers are not writing that extra copy themselves.
First spotted. Darcy Burk, understandably, was not pleased with this update.
Recently, I’ve been delving into an intriguing study by Lily Ray, which reveals some unexpected findings about Google’s AI Overviews. Apparently, these Overviews frequently reference brands’ own listicles but tend to recommend their competitors.
The study highlighted that Google AI Overviews cited these self-promotional listicles in a whopping 69% of B2B software-related queries. Yet, they favored rival brands in their recommendations. This got me thinking about the strategies brands employ to influence AI search outcomes.
Detailed Findings. I discovered that the analysis was quite comprehensive. Ray reviewed 100 B2B queries spanning categories like “best [category] software.” She gathered data across three specific periods: April 15, May 15, and June 8.
The study found that out of 80 queries that triggered an AI Overview, self-serving listicles were referenced 323 times, yet in 224 instances, Google didn’t actually recommend those brands. This mismatch intrigued me.
Analysis of Recommendations. While examining specific cases, it became evident that Google sometimes cited a brand’s listicle but opted to recommend more renowned competitors instead. For instance, in the search for “best LMS for selling courses,” Oasis LMS was mentioned, yet Kajabi and others were pushed forward as the preferred options.
This pattern wasn’t just isolated to LMS software; it appeared in multiple domains like help desk tools, task management, and more. It made me ponder over the dominance of stronger brands in recommendations.
Observing Organic Declines. An interesting trend noted was a drop in organic visibility for websites heavily leaning on self-promotional listicles. I noticed beginnings of these declines back in January and observed further drops post-Google’s May 2026 core update.
Interestingly, these sites also seemed to have expanded into AI-generated content and other “best” pages prominently featuring their own brands.
Rise of Third-party Citations. Ray’s analysis also showed an upsurge in Google comprising third-party content for “best” queries. Platforms like Reddit, Forbes, and YouTube gained traction in citations.
Understanding Impact. I believe it’s crucial to realize that merely having your content cited doesn’t equate to a recommendation. This situation offers competitors the chance to snag attention and, ultimately, valuable visibility.
Keeping Up with Changes. Previously, Search Engine Land shared insights on how some SaaS and B2B businesses witnessed visibility losses after banking on self-ranked “best” lists. The risks are significant when company-driven content doesn’t transparently disclose material relationships as mandated by the FTC’s Consumer Review Rule.
About Ray’s Data. To reach her conclusions, Ray employed Ahrefs Brand Radar to examine numerous AI Overview responses. Her analysis spanned 100 B2B software queries, focusing on citations versus actual recommendations.
Hi there! Today, I’m thrilled to share some intriguing news about Google and its latest venture into AI-powered search advertising. Google has kickstarted testing for healthcare ads in AI Mode. This exciting development gives us a glimpse into the future of advertising within AI-based search environments.
The scope of this test is currently narrowed to healthcare advertisers in the United States and focuses only on English-language queries in AI Mode, as confirmed by Google Ads Liaison Ginny Marvin.
Amidst swirling industry rumors, it has now been officially confirmed that healthcare ads have indeed begun appearing in AI-generated search results.
What Google is saying. Addressing inquiries on LinkedIn, Marvin highlighted that Google has “begun a small test of ads in AI Mode specifically for the healthcare sector.” It’s an intriguing move, isn’t it?
She mentioned that a variety of campaign types can participate, including:
Performance Max (PMax)
AI Max with search term matching
Shopping campaigns
Broad match campaigns
These campaign types can also show ads within AI Overviews.
Why we care. As healthcare stands as one of Google’s stringently regulated advertising sectors, this test is crucial for understanding how Google might monetize AI-driven search results. If the test expands, healthcare marketers could gain a new platform for visibility, and advertisers in similarly regulated industries might get a sneak peek of future ad appearances in Google’s AI-generated search.
The fine print. This initial testing phase comes with some creative boundaries. Marvin noted that ads devoid of pinned assets or text disclaimers are presently the only eligible healthcare advertisements.
What to watch. It’s just the beginning, and we’re curious to see if Google will broaden the eligibility for more healthcare ads, introduce other ad formats, or extend into other regulated fields.
Such developments could provide early clues about Google’s strategy to harmonize monetization and user trust as AI Mode starts to play a more significant role in the search experience.
First spotted. Interestingly, it was Senior Strategist Ben Goldman who first noticed this test, which he shared in response to her GML 2026 summaries on LinkedIn.
I recently came across some exciting updates from Google that are designed to enhance the way we search for and interact with content. Google is introducing new features to its AI experiences, including AI Mode and AI Overviews, by incorporating preferred sources along with a perspectives carousel and highly cited labels.
Preferred Sources in AI Mode and AI Overviews. One of the updates brings preferred sources to AI search results. According to Duncan Osborn, Product Manager at Google Search, users will now be able to easily identify links in AI responses from sources they have selected. I find this particularly beneficial as it helps me quickly access content from sources I trust.
I saw Google testing this feature recently, and now we have the final version that’s rolling out. There will be a label highlighting preferred sources within AI results, making it noticeable to us. It’s fascinating how this is now available globally and in all languages. Google mentions that users have selected over 345,000 unique sources, and these sources receive double the click-through rate. For those interested in trying it out, you can find more details in Google’s documentation.
Perspectives Carousel. Another interesting addition is the perspectives carousel. Google will present a new carousel for certain searches, tailored to help us dive deeper into specific topics, especially when they’re rapidly evolving. The carousel will prominently feature our preferred sources, making recent articles more accessible across various search queries.
In addition to this, there’s also a carousel that shows helpful perspectives from online discussions, forums, and social media. This is a wonderful way for us to tap into diverse viewpoints, broadening our understanding of topics that interest us. These features are being rolled out in AI Mode and AI Overviews.
Highly Cited Label. Finally, Google is expanding the highly cited label to more web article links within search results. This feature makes it easier to find articles that many other stories refer to. It’s a fantastic tool for me to trace a story back to its primary reporting, ensuring that I am viewing the original source of information. This feature will be available across Google Search, beyond just AI-specific functions.
As I immerse myself in Google’s latest guidance on AI search optimization, it’s hard not to approach it with a healthy dose of skepticism.
Whenever Google releases a new Search Central document, our industry splits into two predictable groups. The first group eagerly screenshots the content to share on LinkedIn, captioning it with “SEE? IT’S JUST SEO” before returning to their usual practices. In contrast, the second camp underscores their posts with, “Here’s proof they’re deceiving us,” treating Google’s words as gospel as long as it supports their pre-existing beliefs.
Recently, Google updated its guide on optimizing websites for generative AI features. The “it’s just SEO” advocates had much to celebrate. Many emerging concepts were downplayed or outright dismissed by the guide, reinforcing their belief that not much has changed over the years.
Yet, I can’t help but recall the critical insight we gained a couple of years back from leaked internal documents. Those leaked papers revealed discrepancies between Google’s public messages and what their internal documentation actually detailed. Despite public denials, these documents showed certain signals were very much a part of Google’s algorithms. This reinforces the need for caution in taking Google’s public directions at face value.
I’m not suggesting everything in Google’s new guidance is misleading, but it’s important to note Google’s tendency to push the industry towards its own interests first, possibly benefitting the open web as an afterthought. Google’s narrative drives SEOs to maintain the web’s infrastructure rather than moving towards a more independent approach across diverse platforms.
In my previous discussions about chunking, I’ve highlighted how Google’s influence is waning, as competitive AI platforms redirect user attention. Google’s once-dominant definition of “good content” is now challenged, as evident in their increasingly protective language.
Meanwhile, over at Microsoft, Bing is taking a different approach, transparent about changes and offering publishers insights and tools to optimize their content’s performance in AI responses.
For instance, in their posts, Bing describes the transition towards Generative Engine Optimization and provides practical tools for users, something Google hasn’t quite matched.
So, let’s discuss Google’s claims point by point:
“Is SEO still relevant for generative AI search?”
The idea that “it’s just SEO” is overly simplistic. SEO encompasses more than a collection of tactics; it includes strategic thinking and organizational presence. SEO has been evolving beyond basic practices to influence broader content strategies, yet it is often still underestimated as a supportive task.
This pattern has persisted across various developments, from mobile and voice search to schema and AMP, all initially labeled as merely “SEO.” Each innovation triggers more work for SEO professionals without an equivalent increase in resources.
The skill set and audience have diversified. Traditional SEO targets machine and human users differently than AI Search, which also caters to systems that might bypass traditional site visits altogether.
New labels, like AEO and GEO, can prioritize budgets and attention towards such progressive approaches, unlike the catch-all label of SEO.
When AI Search is recognized distinctly within organizations, it can catalyze cross-functional collaboration and sponsorships that SEOs have long sought.
Despite the extra responsibility placed on practitioners, aligning AI Search under the SEO umbrella usually doesn’t come with new resources or authority, which limits growth and innovation.
Google’s approach, treating all work as “just SEO” rather than recognizing unique systems like AI Mode or AI Overviews, simplifies the real diversity within their technologies.
Non-commodity content is key. Creating valuable and unique content is universally acknowledged as a good practice.
llms.txt files are beneficial, even if Google doesn’t require them. They serve other systems and therefore should be considered in a broad strategy.
Ignoring the multi-platform dynamics leaves a business vulnerable to losing ground where other systems are gaining traction.
Understanding that Google’s public guidance is tailored to its interests rather than offering generalized best practices across all platforms is crucial for developing a robust SEO strategy in this new era.
Google’s recommendations are one perspective in a rapidly evolving landscape where multiple opinions and infrastructures are emerging.
Stay informed, apply what’s relevant, but don’t take any single source as absolute truth. We’re navigating a new world requiring attention to diverse strategies to succeed across platforms.
First published on the iPullRank blog, republished here with permission.
When I attended Google Marketing Live 2026, I witnessed firsthand how Gemini is reshaping the world of Search, advertising, commerce, and measurement. The event highlighted the move towards a more conversational, AI-driven ecosystem.
This year, the focus was on agentic AI, conversational Search, automated creative production, and AI-assisted shopping. Google rolled out tools across Search, YouTube, Merchant Center, and Analytics aimed at making campaigns more autonomous, predictive, and interconnected.
Let me take you through the biggest announcements from Google Marketing Live 2026.
Google Introduces a New Generation of AI-Powered Search Ads
Google rolled out new Gemini-powered ad formats that enhance AI Mode and conversational Search experiences.
The updates include:
Conversational Discovery ads
Highlighted Answers
AI-powered Shopping ads
Business Agent for Leads
These innovative formats are crafted to be more contextual and interactive by embedding AI-generated explanations and conversational experiences directly into Search journeys.
Plus, Google expanded its Direct Offers pilot with AI-generated bundles, native checkout, and travel promotions seamlessly integrated into AI-assisted Search experiences.
Google Launches Ask Advisor Across Ads, Analytics, and Merchant Center
At the event, Google introduced Ask Advisor, a Gemini-powered AI collaborator that bridges Google Ads, Analytics, Merchant Center, and the Google Marketing Platform.
It functions as a unified assistant to help marketers:
Build campaigns
Analyze performance
Receive recommendations
Automate operational tasks
Google assures that Ask Advisor expedites the process from planning to optimization by pulling insights across platforms.
Google Upgrades Measurement with Meridian and Predictive AI Tools
Google announced new tools for measurement and forecasting within Google Analytics 360.
Meridian, an open-source marketing mix model, is being integrated directly into Analytics 360, along with Qualified Future Conversions (QFCs), a predictive reporting metric powered by Gemini.
These tools will assist advertisers in:
Improving media mix modeling
Forecasting campaign outcomes
Measuring incrementality
Linking current ad activity with future revenue signals
Today, I’m excited to share that Google is taking a significant leap forward in the world of online shopping by expanding its Universal Commerce Protocol (UCP). This comes with a host of AI-powered checkout and payment features designed to enhance conversational commerce experiences.
At the recent Google Marketing Live 2026 event, they unveiled these exciting new features. One of the highlights is the Universal Cart. It lets me save products from multiple retailers and complete my purchases effortlessly using Google Pay or the retailer’s own checkout system.
It’s thrilling to see major brands like Nike, Sephora, Target, and more jumping on board. They’re also integrating UCP into AI Mode shopping experiences and their ads on platforms like YouTube.
Furthermore, Google’s new partnerships with Affirm and Klarna for buy-now-pay-later options integrated into Google Pay bring a fresh breath of convenience to shoppers like me.
Universal Commerce Protocol connects product catalogs, checkout, and payment experiences seamlessly across Google’s surfaces, including Search and Maps. Soon, I can expect it to support hotel bookings and food deliveries, which means even more convenience for us end-users.
As an avid online shopper, I appreciate how Google is making strides towards enhancing AI-driven commerce. They’re set to reshape how brands like mine will structure product feeds and promotional strategies.
Currently, these new UCP-powered features are rolling out in the U.S., and I’m eagerly waiting for their expansion to more countries, including Canada and the U.K.
To delve deeper into what unfolded at Google Marketing Live, check out updates on innovations like conversational ad formats and Google’s AI-driven tools in their Merchant Center.
Today, I’m thrilled to share that Google has unveiled exciting new tools in the Merchant Center, all geared towards boosting retailer visibility on AI-driven shopping platforms. Announced at Google Marketing Live 2026, these tools are set to transform how products are discovered.
Driving the news. Let me introduce you to AI Performance Insights, a fresh reporting feature that gives merchants a snapshot of their brand’s performance across AI platforms.
This handy tool lets me compare my brand’s share of voice with similar competitors, ensuring I stay on top of AI-driven discovery metrics.
Google is also introducing Conversational Attributes, enhancing how we optimize our product listings to align with natural, conversational searches.
How it works. I can now add conversational attributes and update descriptions directly in the Merchant Center. Google’s AI can utilize this structured data to meet conversational search queries seamlessly across AI Mode, Gemini, and other AI platforms.
These updates are crafted to enhance discoverability as AI continues to reshape shopping experiences.
Moreover, Ask Advisor integrations are soon to be part of my Merchant Center tools.
Why we care. Structured product data is now more essential than ever as AI shopping experiences proliferate across Search, Gemini, and Maps.
By adapting product descriptions for conversational discovery, I can better position my products within AI-generated recommendations and shopping paths.
These new reporting tools also give me early visibility into how my brand performs in AI-powered environments.
What to watch. With the rise of conversational search behavior, optimizing product feeds for AI visibility is becoming increasingly critical. I’ll also be keeping an eye on how Google defines and measures “share of voice” within these AI-powered shopping ecosystems.
Availability. AI Performance Insights will soon roll out in the U.S., Australia, Canada, India, and New Zealand. Meanwhile, Conversational Attributes are launching globally.
Dig deeper. Here are some more updates from Google Marketing Live 2026:
I’m excited to share that Google has announced some transformative updates to its search capabilities. These updates include the introduction of information agents and enhanced agentic experiences that will elevate how we interact with search. Google’s AI will continuously scan the web, ensuring we receive the most current information, much like a personal assistant would.
In a recent announcement, Google revealed new search agents, focusing on information agents and additional agentic functionalities within Google Search. These information agents are designed to monitor the web for changes to our tasks, seamlessly supporting us on our journey through various challenges and questions.
Liz Reid, the head of Google Search, stated, “We’re entering the era of Search agents, where you can easily create, customize, and manage multiple AI agents for your many tasks, right in Search.” This new era provides a unique opportunity to tailor search experiences to our specific needs.
Information Agents. These agents are designed to keep us informed about our questions and tasks. Google’s agents will intelligently sift through the internet—exploring blogs, news sites, social posts, and accessing the freshest real-time data on finance, shopping, and sports, to ensure we receive the most relevant updates on our inquiries.
The information agents will then compile an “intelligent, synthesized update” that not only provides the necessary information but also enables us to take action.
The Example. Envision yourself apartment hunting. You can simply input all your specific requirements, and your agent will continuously scan listings, alerting you whenever a match surfaces. Similarly, if you’re keen on not missing any sneaker collaborations from your favorite athletes, your agent will notify you about new releases.
Availability. These exciting capabilities are set to roll out this summer, initially available to Google AI Pro & Ultra subscribers.
Agentic Experiences. Google is also extending its agentic booking capabilities within Google Search to encompass new tasks like finding local experiences and services. Imagine effortlessly booking a private karaoke room for an exact time and with specific food options, all handled by Google Search.
Google will provide the most current pricing and availability information, along with direct links for purchase, streamlining experiences across various services, including home, repair, beauty, and pet care. These features are expected in the U.S. this summer.
Personal Intelligence Expanding. In addition, Google has revealed plans to broaden its Personal Intelligence feature within AI Mode, now reaching around 200 countries and territories, supporting 98 languages.
Today, I’m excited to share that Google has announced the launch of its latest AI model, Gemini 3.5 Flash. This powerful update is now the default engine for Google’s AI Mode, transforming how we experience search every day.
At the recent Google I/O, I learned about Gemini 3.5 Flash directly from Google’s head of Search, Liz Reid. She described this model as Google’s “newest Flash model delivering sustained frontier performance for agents and coding.” It’s thrilling to know that this technology is now impacting users worldwide.
What really excites me is that 3.5 Flash doesn’t just enhance AI Mode in Google Search; it also powers the Gemini app for everyone, regardless of whether they are paid users or not. It’s great to see Google making such advancements widely accessible.
Developers, you’re in for a treat! 3.5 Flash is now integrated into Google Antigravity, Gemini API for Google AI Studio, Android Studio, and more. For those in enterprise, it’s now part of the Enterprise Agent Platform and Gemini Enterprise.
Koray Kavukcuoglu, CTO of Google DeepMind and Chief AI Architect, shared that Gemini 3.5 Flash rivals the intelligence of large flagship models while providing the speed we expect from the Flash series. It outshines previous models, making remarkable strides in agentic and coding performance benchmarks. I’m truly impressed by its capabilities in multimodal understanding too.
Why should I care? Well, with Gemini 3.5, Google Search’s AI Mode is smarter and more efficient than ever. I’m eager to explore how AI Mode’s responses evolve, especially for the queries that matter most to my site.
The rapid changes in search technology mean it’s crucial to stay informed and adaptable. This update reaffirms the importance of keeping pace with Google’s innovations.
