As someone deeply interested in how technology shapes our interactions, I found Google’s new AI developments in search particularly fascinating. Google’s VP of Search, Liz Reid, recently delved into how AI is transforming search intent, monetization, and content visibility. In a new Bloomberg podcast, she explained how these changes are reshaping our search behavior.
Reid assured us that AI is not diminishing Search but altering its usage. AI Overviews now help filter low-value clicks while encouraging more frequent searches. Reid highlighted how AI reduces “bounce” clicks, those quick visits to a page for a single fact. It’s an interesting evolution—sometimes we only have seconds to spare, while other times, we aim to immerse ourselves for longer periods.
People Want AI and the Web Together
Reid debunked the myth that users desire AI over the web. Instead, she notes, people want AI integrated into their web experience. I see this pattern in my own browsing habits, where I might search for a quick fact one moment and dive deeply into an article the next. She emphasized that people still crave human perspectives and diverse insights.
AI Overviews: Adapting to User Needs
Liz Reid explained that AI Overviews aren’t activated for every search. Google’s strategy is user-centric, providing AI support only when it’s beneficial. This selective approach ensures we get the best possible answer for our queries. The system evolves as user behaviors change, and Google continually refines which queries deserve an AI Overview.
Changing Search Habits
It’s intriguing to note the shift in how we query Google. Searches have become longer and more conversational, moving away from terse keywords. In my own searching, I now use full sentences to express my needs, which aligns with Reid’s insights. She reiterated that users now articulate their problems more clearly, allowing Google to provide comprehensive responses.
Ads and AI: A New Dynamic
Even with AI-enhanced answers, Google can still generate revenue from Search, assuring us that the commercialization of queries largely remains unaffected. When I’m on the hunt for products, such as buying shoes, I still rely on ads to guide my purchasing decisions. Reid also highlighted that detailed queries offer potential for more targeted ads.
Monitoring User Retention
Reid highlighted that a key metric for Google is whether users return to Search more frequently. This is more than just increased search volume; it’s about building a loyal user base that turns to Google consistently because it meets their needs effectively.
AI Slop: Addressing Content Quality
Interestingly, AI hasn’t introduced new content quality issues but rather increased its volume. Reid assured us that Google’s aim is to spotlight quality content while minimizing the visibility of “slop.” It’s a challenge, but one that Google is committed to tackling by continually enhancing its ranking systems.
I recently discovered that Google is quietly testing something quite intriguing—a new “App Labs” beta in Google Ads. This development is offering app advertisers early access to experimental campaign features before they’re available to everyone.
What’s new? There’s a new dedicated tab within the App advertising hub. Here, advertisers like me can explore limited-time experiments, provide valuable feedback, and take a sneak peek at tools still in development.
Why do I care? Well, Google providing early access means I get a chance to test, learn, and optimize before competitors catch on. This early adoption could give my advertising efforts a significant performance edge, helping me adapt more quickly as new tools standardize.
Zoom in. Features in App Labs are essentially short-run tests. They’re not guaranteed to roll out on a permanent basis, but they offer Google real-world feedback while giving me a first-mover advantage.
Between the lines. This is essentially a sandbox for app campaigns and signals that Google values advertiser input early in the product cycle.
What to watch. As an early adopter, I might see performance advantages by testing and adapting to features long before my competitors are even aware of them.
First seen. I first heard about this update from Google Ads expert Thomas Eccel, who spotted it and shared the news on LinkedIn.
I’ve noticed that Google is currently investigating an issue with the Google Search Console. Specifically, this concerns the data logging and reporting of “Job listing” and “Job details” search appearance filters.
On April 16th, a bug began affecting how this data is logged, causing Google to report zero clicks and impressions for job-related reports. Although traffic is still being received, it’s not being recorded correctly.
What Google said. According to an update from Google, “A logging error is preventing Search Console from reporting impressions and clicks for ‘Job listing’ and ‘Job details’ Search appearance types from April 16, 2026 onward. We’re working to resolve this issue. This issue affects data logging only.”
Complaints. I’ve also seen numerous SEOs voicing their concerns on social media, as shared in a tweet by Max Peters. The bug seems to impact impressions and clicks, but the traffic still comes through other measurement methods like google_jobs_apply UTM.
Why we care. If you’ve noticed a decrease in search data for job listings, rest assured, it’s due to this bug on Google’s side. Your listings are likely still active and receiving traffic, although this isn’t reflected in Search Console at the moment.
Have you heard the news that OpenAI has introduced CPC ads to ChatGPT? This strategic shift has transformed it into a performance-driven channel, offering advertisers new avenues for engaging intent-driven audiences and tracking ROI.
OpenAI is moving away from a focus purely on impressions in ChatGPT to prioritize performance. This change places OpenAI in direct competition with giants like Google by adopting cost-per-click (CPC) ads, allowing advertisers to pay only when users click on their ads.
What’s happening? OpenAI has started testing CPC ads within ChatGPT, where advertisers only pay when their ads receive clicks. Initial reports highlight that these clicks are priced between $3 to $5. They’re rolling out this feature through a limited ads manager, alongside their existing CPM-based model.
Why now? The main catalyst seems to be pricing pressure. Since its launch, ChatGPT’s CPMs have significantly decreased from around $60 to approximately $25. Switching to CPC helps mitigate this decline by connecting revenue to tangible outcomes rather than mere impressions.
Why do we care? With its evolution into a performance channel, ChatGPT is now not just a branding space. The CPC pricing model makes it easier for us to connect budgets directly to measurable actions, test ROI, and compare these results with channels like Google Search.
I’m excited about the opportunity for advertisers to access what could be a high-intent audience in a new format. This presents a first-mover advantage before competition—and the associated costs—escalate.
The bigger picture: This isn’t just a pricing change; it’s a strategic pivot. By embracing CPC advertising, OpenAI challenges Google’s dominance in the market, thereby positioning ChatGPT as a contender for performance marketing budgets.
Reading between the lines: A major challenge lies in proving user intent. While search advertising is effective because it captures users actively searching for something, ChatGPT’s conversational context needs to generate clicks with equal value. Advertisers will likely compare these results directly with Google, setting a high standard for quality and conversion.
Zoom out: Advertising is becoming integral to OpenAI’s long-term revenue plan, supported by investments in ad infrastructure, measurement tools, and a wider self-serve platform.
Bottom line:By implementing CPC ads, OpenAI is vying for the performance-driven ad dollars that have long supported traditional search platforms.
I recently came across OpenAI’s testing of a new ChatGPT Ads Manager interface, which heralds a promising shift towards a more scalable and self-directed advertising platform.
Advertisers are buzzing about their experiences with the new Ads Manager interface for ChatGPT. It’s a leap forward, offering a mature advertising platform where we can manage campaigns in real time. This is a significant improvement over what we’ve had so far in terms of reporting and controls, as shared by digital marketers Juozas Kaziukėnas and Glenn Gabe through their detailed images.
What’s New: The Ads Manager is essentially a dashboard that allows me to run, monitor, and optimize campaigns in real-time—a significant advancement from the limited reporting we’ve seen previously. Juozas Kaziukėnas and Glenn Gabe shared some fascinating insights through images of this evolving interface.
Why It Matters: Up to now, ChatGPT ads have been in the nascent stages, with advertisers relying on basic tools like weekly CSV reports. The introduction of a comprehensive Ads Manager indicates OpenAI’s efforts to construct an infrastructure analogous to what we see in platforms like Google Ads or Meta.
Zoom In: I’m noticing more ads popping up inside ChatGPT, with brands such as Best Buy and Expedia being visible in early tests. The increase in ad inventory, combined with a sophisticated management interface, suggests a swift expansion in monetization endeavors.
What to Watch: As the Ads Manager continues to evolve, I’m looking forward to more refined targeting, reporting, and automation features. Initial feedback indicates there’s still room for growth here, especially concerning ChatGPT ads.
First Seen: Glenn Gabe was among the first to share glimpses of the ChatGPT ads manager interface on X.
I’ve got some exciting news about Google Ads: They’ve introduced something called App Consent Insights! This new feature aims to give us, the advertisers, a much clearer picture of how consent affects our app campaign performance.
What’s new? There’s this cool diagnostics view that breaks down consent data across various apps, platforms, regions, and traffic sources. It’s a game changer for understanding where we might have gaps in our setup.
Zoom in. I can now see an overall consent rating described as “Excellent,” “Good,” or “Poor.” Plus, there’s a live count of apps actively sending consented data and a detailed table that shows consent rates for conversions, including the differences between EEA and non-EEA users.
Why it matters to us. With privacy regulations getting stricter, consent isn’t just a compliance issue—it’s a critical factor for measurement and optimization. This update gives us more visibility into how consent setups could be holding back our performance.
Between the lines. Google is making it easier for us to measure and act on consent data at a time when signal loss significantly impacts campaign performance.
What to watch. We should start looking at optimizing not just for conversions, but also for improving consent rates as another lever of performance.
Bottom line. With better visibility into consent, we can achieve better data quality and ultimately, better campaign outcomes.
First seen. Google Ads expert Thomas Eccel first noticed this update on LinkedIn.
Recently, I discovered that Google has made some significant changes to how it paces budgets for Google Ads campaigns with ad schedules. The company is now ensuring that it uses the full monthly budget, even if the ads are not running every day.
What’s Changing Starting June 1, campaigns will pace toward spending the entire monthly budget limit (30.4 times the daily budget) regardless of the ad schedule. Previously, the pacing was dependent on how many days ads were active.
What’s Not Changing Things such as daily and monthly spending caps remain untouched. Campaigns will still not exceed double the daily budget in one day or 30.4 times the daily budget over the course of a month, ensuring ads won’t run on disabled days.
Why It Matters Advertisers who utilize limited schedules, like running ads only on weekdays or during specific hours, might notice accelerated spending. Google is now determined to reach the entire monthly budget, rather than scaling back on days ads can run.
Zoom In This modification means that campaigns with fewer service days could see a more aggressive spend on those active days. For instance, if ads only run for half the month, Google can still spend up to the daily maximum each day without needing to economize elsewhere, all the while staying within the monthly cap.
Between The Lines This approach appears to prioritize maximizing budget utilization over evenly distributing spend, giving Google’s systems enhanced flexibility to capture demand when campaigns are active.
What To Watch If you have tight schedules, you may need to reconsider your budget allocations and performance expectations, as spending could be more concentrated on active days.
Bottom Line Budget pacing is shifting focus from when ads are posted to ensuring the budget is fully utilized each month.
First Seen Several advertisers hinted at receiving communications from Google regarding this, but Google Ads Coach Jyll Saskin Gales provided more clarification through LinkedIn.
When I think about brand visibility today, it’s clear that being chosen by AI systems is crucial. Authority, unique insights, and consistent signals now determine if my brand makes the cut.
I’ve realized that AI isn’t just reshaping search; it’s deciding which brands are seen and which are ignored.
I learned from Andrew Warden, CMO of Semrush, at the Adobe Summit that visibility is evolving fundamentally, and our brands risk being systematically filtered out by AI systems.
“The idea of standing out is no longer optional. There’s a real risk of sameness,” he pointed out.
With AI systems deciding what to highlight and what to ignore, I know I must compete more fiercely for visibility in AI-generated answers.
AI is Changing How Discovery Works
The change is evident in the data: 60% of Google searches now end without a click to a website. People are still seeking information but aren’t always visiting websites. They’re getting their answers directly from AI systems like Google AI Overviews and ChatGPT.
These AI systems have become, as Warden described, the “new gatekeepers.”
This shift ushers us into the agentic era, where AI systems act as intermediaries, guiding users from inquiry to decision in one seamless interface.
Meanwhile, user behavior is evolving. People engage more in conversational environments, posing follow-up questions, refining queries, and surveying options within the interface, all resulting in fewer clicks but often attracting higher-intent users.
Warden noted that consumers using LLMs convert at least four times higher than those relying solely on search.
SEO is the Foundation
Despite some claims that AI could replace search, Warden reassured us that SEO is not dead.
SEO has become more foundational than ever. It’s essential to ensure my brand exists in the data layer AI systems rely on.
Warden emphasized, “SEO isn’t just for humans anymore. This is a training manual for AI right now.”
This involves ensuring:
Crawlability
Indexability
Structured data
Authority signals
Without these, my brand won’t appear at all.
Research backs this up: 94% of Google AI Overviews cite at least one top organic result, reaffirming that traditional search signals still support AI outcomes.
The Rise of the ‘Bland Tax’
One striking concept from the session was what Warden dubbed the “bland tax.”
AI conditions itself to overlook blandness, causing generic or repetitive content to vanish.
If I’m generic, Warden warned I’m perceived as average, and if I’m bland, I’m effectively invisible.
AI systems don’t reward sameness. Rather than highlighting my brand, they often condense similar content into a single, attribution-lacking response.
“This is an invisible penalty,” Warden noted.
The consequences manifest in several ways:
My brand identity gets erased in AI-generated summaries
My content is filtered out as low-value
My work becomes training data for AI without offering visibility to my brand
“You also become a free training ground for LLMs,” he said.
What Visibility Depends On
Warden redefined brand visibility as a blend of:
Discoverability: Can LLMs easily find me?
Authority: Do they trust my brand enough to include it?
“You absolutely need both,” Warden asserted.
SEO ensures I’m discoverable. Authority determines whether my brand shows up in AI-generated responses.
Without authority, I risk turning into a “commodity that isn’t worth being mentioned.”
How to Win: Three Key Signals
Warden outlined three crucial areas determining whether my brand appears or gets filtered out:
1. Entity Authority
AI systems map entities and relationships, and they must recognize my brand as an authority on a topic.
One key signal is brand demand. If people aren’t seeking out my brand, neither will AI.
Strong brands emphasize their authority across various platforms—owned content, media exposure, and community discussions—demonstrating their niche.
2. Information Density and Originality
AI systems prioritize content that offers new insights. It’s vital to not just publish content but contribute something meaningful.
They emphasize new facts with proprietary data, original research, unique perspectives, and expert insights.
According to Warden, original insights can enhance visibility by 30 to 40%.
3. Signal Alignment
AI evaluates not just what I convey but also what others say about my brand.
This includes reviews, discussions on platforms like Reddit and YouTube, media mentions, and customer conversations.
Warden warned that conflicting signals could prompt AI to flag my brand as unreliable.
Consistency across these channels creates what he called a “consensus signal” that AI systems can trust.
Why Most Organizations Aren’t Ready
One of our biggest challenges is organizational, as visibility isn’t just a channel issue; it’s an organizational one.
Currently, responsibilities are fragmented. SEO teams focus solely on rankings, PR and brand teams manage messaging, and growth teams conduct experiments. This leaves no one clearly owning AI visibility.
This fragmentation leads to inconsistent signals and missed opportunities for us.
To truly compete, we need alignment across teams, working on a shared strategy about how my brand appears wherever LLMs gather data.
The Measurement Problem
Meanwhile, traditional performance metrics are unraveling.
Many marketers, including myself, notice a gap where rankings hold steady, but traffic declines. Meanwhile, leads might increase, yet attribution remains murky.
Warden explained that demand remains, but traffic no longer serves as its proxy. Our content is utilized, but not in ways directing users back to us.
This creates a growing disparity between impact and the ability to measure that impact accurately.
From Rankings to Relevance
The nature of competition has evolved. I’m no longer vying for a mere position; instead, I’m competing to be featured in a synthesized AI answer.
Authority, once easier to influence, now hinges on external validation—emphasizing what others say over what I publish.
Algorithms have shifted from being my allies to arbiters of meaning, marking a significant change in search dynamics since Google itself emerged.
The New Rules of Brand Visibility
AI has not altered what makes a brand strong but has transformed how that strength is measured and rewarded. The brands that win today will build real authority in a focused niche, publish original and high-value content, and ensure consistent messaging across every platform.
The need for consistent third-party validation across an ecosystem is paramount.
As Warden urged, I must make it impossible for LLMs to ignore my brand.
I’ve recently discovered that Google has introduced some exciting AI safety features in their Ads Advisor, which could really transform how we manage campaigns. This update promises to automate policy fixes, enhance security, and expedite certifications, all to help us run our campaigns more efficiently.
As someone who spends a lot of time tackling policy issues and managing certifications, this news is music to my ears. With advertising campaigns becoming increasingly complex, having AI handle these time-consuming tasks could significantly boost our productivity and performance.
What’s New. The latest update brings proactive troubleshooting, continuous security monitoring, and immediate certifications. Thanks to AI and Google’s Gemini capabilities, these features promise to be a real game-changer.
Zoom In:
Ads Advisor can now automatically flag and resolve policy violations before they even catch our attention. This proactive approach ensures we stay ahead of potential issues.
The new security dashboard is always on the lookout for risks such as suspicious domains or dormant users. It’s like having an ever-vigilant guard protecting our accounts 24/7.
Imagine getting certifications that used to take weeks, approved instantly with just a click. This means we can focus on strategy rather than paperwork.
How It Works. Ads Advisor proactively scans accounts and sites, offering up fixes and confirming resolutions without the need for manual intervention. On the security front, it continuously checks account health and even supports passkey use, reducing our dependency on passwords.
Why We Care. These features save us hours that were once spent fixing issues, upping our security game, and dealing with certifications. This proactive system reduces delays and risks, ultimately enhancing campaign speed and efficiency.
What to Watch. Google plans to roll out these features for English-speaking accounts over the coming months, with additional languages to follow.
I recently came across a fascinating discussion at the Adobe Summit, where Alexis Zamkow and Sandhya Ranganathan Iyer from IBM highlighted the urgent need for brands to modify their approach to SEO. As AI revolutionizes the way brands are discovered, IBM has developed a 12-part GEO playbook that every brand should consider to remain visible in AI-generated decisions.
The evolution of search is something I’m experiencing firsthand. AI tools now answer questions, compare products, and recommend brands without users even needing to visit a website. This means that if my brand isn’t included in this AI-generated narrative, I’m potentially out of the picture when decisions are made.
To stay relevant, merely updating tactics won’t suffice. A holistic system, namely a GEO (Generative Engine Optimization) playbook, is key. During their presentation, aptly named ‘Adapt or Disappear: How Brands Win with AI-Powered Search,’ Zamkow and Iyer emphasized this shift.
Embracing the AI Shift: Marketing to Machines
I’ve realized that AI agents now mediate the interaction between me and my customers. They simplify complex markets and often represent my brand to potential customers.
As Zamkow aptly put it, “These machines are disintermediating the brand experience.”
In this new landscape, consumers heavily rely on AI for research and decision-making, businesses are quick to adopt AI solutions, and many searches conclude without any clicks.
Zamkow estimates that in the next couple of years, AI agents could account for 75% of search visibility, highlighting the importance of being included in the AI-generated answers themselves.
The GEO Playbook: 12 Essential Components
To navigate this shift, the speakers unveiled a 12-part playbook focusing on content, technology, and operations. It starts with creating a strategic content foundation which ensures that my messaging is clear and consistent across all platforms, building trust for both users and machines.
Ensuring my content meets retrieval-grade passage standards is crucial. Since AI extracts answers rather than ranking webpages, content clarity is key. I need to present information in concise, easy-to-understand sections.
Technical foundations can’t be ignored. It’s essential that my content is machine-readable with clean HTML, structured data, and pages that load content directly to maximize AI extraction.
I started by optimizing my on-site search to align with GenAI, making sure it can easily find relevant answers — a foundation for external AI search visibility.
Equally important is the AI search citation qualification model. Not just being mentioned, but cited by AI, boosts trust and credibility through consistent messaging and recognized expertise.
Through extraction optimization, I ensure my content is structured and rich in context to be easily pulled by AI tools.
Understanding that 85% of mentions come from external domains, I focus on a third-party strategy involving content mentioned across platforms like Reddit and social media, recognizing that PR and social teams are critical for search success.
Tracking new KPIs, such as AI mention frequency and citation locations, becomes essential, shifting my focus from mere traffic to AI recommendations.
I implement SOPs to maintain consistency in how my content is written, structured, and published, preventing confusion for AI systems.
With searches becoming conversational, I adopt prompting best practices, crafting content that aligns with users describing their queries in a more natural way.
Managing change across the entire organization involves training, goal alignment, and breaking down silos, emphasizing that this evolution is more than a marketing update; it’s transformational.
Continuous governance and versioning are critical. AI and competitor content change rapidly, making it vital to monitor, update, and maintain ownership of content changes.
From SEO Tactics to Comprehensive GEO Systems
We’re moving beyond traditional SEO, transitioning from keywords to prompts, links to citations, and from traffic-based metrics to validating our presence in AI answers. Importantly, it’s about building a system to continuously supply AI with accurate information.
A Leadership Issue
This transformation is rapidly becoming a leadership concern. As shared by Zamkow, this is no longer solely a matter for the SEO team; it’s a priority for CEOs, who need to recognize the importance of brand visibility in AI-based recommendations.
Adapt or Disappear
The AI-driven world is reshaping brand discovery. It’s trusted by consumers, utilized by businesses, and expanding quickly. Brands prepared with a comprehensive GEO playbook are poised to maintain visibility, while others risk being invisible in the digital landscape.
