The third and likely final core update of 2025, the December 2025 core update, is now rolling out and complete. It started on December 11, 2025 and was completed about 18 days and 2 hours later on December 29, 2025. Google called this update “a regular update designed to better surface relevant, satisfying content for searchers from all types of sites.”
“This is a regular update designed to better surface relevant, satisfying content for searchers from all types of sites.”
What we saw. The initial rollout touched down within a few days after the update was announced, specifically on December 13, 2025. Then on December 20th, we saw another big spike in volatility. Like with all core updates, some sites saw huge declines in ranking visibility, some saw some big improvements and many saw no changes.
I’d also recommend you watch this video from Glenn Gabe on the December core update.
What to do if you are hit. Google did not share any new guidance specific to the December 2025 core update. However, in the past, Google has offered advice on what to consider if a core update negatively impacts your site:
There aren’t specific actions to take to recover. A negative rankings impact may not signal anything is wrong with your pages.
Google said you can see some recovery between core updates, but the biggest change would be after another core update.
In short: write helpful content for people and not to rank in search engines.
“There’s nothing new or special that creators need to do for this update as long as they’ve been making satisfying content meant for people. For those that might not be ranking as well, we strongly encourage reading our creating helpful, reliable, people-first content help page,” Google said previously.
Why we care. Now that this December 2025 core update is done, you can start to dig in to see how you are your clients were impacted. You can review Google’s guidance and continue to improve your site, which hopefully will lead to better Google ranking in the future. Google releases core update every few to several months, so you should always continue to work on improving your site and the content on your site.
I hope you all did well with this last Google update and you all have an amazing holidays and new years!
Video summary. Here is a video summary I made on this core update:
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/12/sno6z4qafnu-s9neNi.jpg?fit=1280%2C720&ssl=17201280http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-12-29 19:10:552025-12-29 19:10:55Google December 2025 core update rollout is now complete
Google launched four official and confirmed algorithmic updates in 2025, three core updates and one spam update. This is in comparison to last year, in 2024, where we had seven confirmed updates, then in 2023, when we had nine confirmed updates and in 2022 and 2021, Google had 10 confirmed algorithmic updates.
Fewer updates. Google appears to be confirming fewer updates, even though Google said a year ago, that we should expect more core updates, more often. But that doesn’t mean there were fewer updates. Google did reaffirm that it does not announce all core updates, that the search company only confirms the larger, broader core updates.
Plus, I covered dozens of unconfirmed Google updates on the Search Engine Roundtable. It was a super volatile year, even without Google confirming as many algorithmic search updates.
Google confirmed algorithm update summary
We whipped up this timeline documenting all the confirmed Google search algorithm updates in 2025, so you can visualize the updates over the year.
Three Google core updates in 2024
Google had three core updates in 20225, four core updates in 2024, the same number as it had in 2023, but in 2022 Google only had two core updates. We had core updates in March, June, and December.
March 2025 core update. The Google March 2025 core update started rolling out March 13, it took 14 days to complete, and finished on March 27. Google told us this core update was a normal core update. Google wrote:
“Today we released the March 2025 core update to Google Search. This is a regular update designed to better surface relevant, satisfying content for searchers from all types of sites. We also continue our work to surface more content from creators through a series of improvements throughout this year. Some have already happened; additional ones will come later.”
The volatility from this update seemed similar to previous core updates – we broke that down over here.
June 2025 core update. The June 2025 core update started rolling out on June 30, it took about 16 days to complete, and finished on July 17. Again, this was a normal broad core update. Google wrote:
“This is a regular update designed to better surface relevant, satisfying content for searchers from all types of sites.”
December 2025 core update. The December 2025 core update started rolling out on December 11, it took 18 days to complete, and finished on December 29. Again, this was a normal broad core update. Google wrote:
“This is a regular update designed to better surface relevant, satisfying content for searchers from all types of sites.”
The volatility was intense but also super calm throughout most of the weekdays. We had two big spikes, both on Saturdays, on December 13th and December 20th.
One Google spam update in 2025
August 2025 spam update. The August 2025 spam update started rolling out on August 26, it took 27 days to complete, and finished on September 22. This update was a general and broad spam update. Google did not announce anything unique with this spam update. Google just wrote:
“This is a normal spam update, and it will roll out for all languages and locations.”
This spam update touched down very quickly, where sites that were impacted by this update saw the results within about 24 hours. It hit hard and fast. Then, around Sept. 9, the update heated up again, with a number of sites noticing ranking fluctuations and indexing issues. While many impacted sites saw steep declines in Google Search organic visibility, some sites that were hit by previous spam updates saw significant recoveries.
Other Google algorithm changes, updates, tweaks or topics
Other Google updates. While we had three core updates and one spam update, Google also pushed out other search specific updates in 2025. Here is a list of those:
This year, Google released AI Mode and expanded AI Mode to more countries and regions throughout the year.
Also, throughout the year, Google released update Gemini models to improve AI Mode and AI Overview responses. The lastest being Gemini 3 Flash, and Gemini 3 Pro.
In June 2025, Google updated its ranking algorithms for explicit videos and content. Google wrote, “If you don’t allow Google to fetch your video content files, Google can’t run automated protections against egregious violations such as CSAM. Content that can’t be fetched may pose a risk to our users, so Google may demote or filter such pages where the embedded video content is unavailable and our automated systems determine that the page may contain explicit content. Not allowing Googlebot to fetch your video files may significantly affect the ranking of your explicit pages on Google Search, and especially in Video mode.”
Google Search bugs. Google also had several search bugs throughout 2025:
In June, Google has a serving issue within Google Search that was short lived.
In August, Google had a crawling bug that took it several days to resolve.
Find out what llms.txt is, how it works, how to think about it, whether LLMs and brands are buying in, and why you should pay attention. (By Rob Garner. Published March 28.)
Learn how SEO and GEO strategies differ – and how combining both can boost your visibility across search engines and AI-driven platforms. (By Dan Taylor. July 28.)
Read this deep dive into six patents that reveal how Google’s AI Overviews and AI Mode work – and what it all means for the future of SEO. (By Michael King. June 2.)
From ChatGPT to Gemini, here’s what each AI model trusts – and how strategic content earns visibility in generative search results. (By James Allen. Published May 12.)
AI search tools are on the rise, but SEO fundamentals remain critical. Learn how the two intersect and what it means for your strategy. (By Lily Ray. Published July 18.)
Your customers search everywhere. Make sure your brand shows up.
The SEO toolkit you know, plus the AI visibility data you need.
Don’t rely solely on tools like Search Console or Screaming Frog. Diversify your toolset with these time-saving Chrome extensions. (By Stephanie Wallace. Published Jan. 16.)
AI platforms are transforming discovery. Traffic is surging. Now strategies must evolve, according to the 2025 Previsible AI Traffic Report.. (By David Bell. Published Aug. 5.)
Why the web as we know it may fade and what AI, personal agents, and data interfaces mean for publishers, SEO, and commerce. (By Mario Fischer. Published Nov. 14.)
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2021/12/web-design-creative-services.jpg?fit=1500%2C600&ssl=16001500http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-12-29 15:00:002025-12-29 15:00:00Top 10 SEO expert columns of 2025 on Search Engine Land
Another year in search has come and gone, and Google called it year three of a 10-year platform shift. In 2025, that shift became impossible to ignore. AI moved from experiments and previews into the core of how search actually works.
Below are the biggest SEO news stories of 2025 on Search Engine Land.
Note: This article doesn’t include any stories related to Google algorithm updates. Barry Schwartz wrote a separate recap on that, which will also publish today.
10. Perplexity ranking factors and systems
Independent researcher Metehan Yesilyurt analyzed browser-level interactions to reveal how Perplexity scores, reranks, and sometimes drops content. He uncovered a three-layer machine-learning reranker for entity searches, manual authority whitelists, and dozens of engagement and relevance signals.
Yesilyurt’s research also found boosts for authoritative domains, strong early performance, and topics centered on tech and AI. Rankings further reflected time decay, interconnected content clusters, and synchronized YouTube trends that increased visibility across platforms.
Your customers search everywhere. Make sure your brand shows up.
The SEO toolkit you know, plus the AI visibility data you need.
Start Free Trial
Get started with
9. Google Search Console Query groups
Google added Query groups to the Search Console Insights report. The feature uses AI to cluster similar search queries into clear audience topics and does not affect rankings. It rolled out gradually to high-volume sites and replaced long query lists with topic-level groupings that make performance shifts easier to spot.
HubSpot’s organic traffic appeared to fall from 13.5 million to 8.6 million in a month, with most of the losses coming from its blog. The drop followed several Google updates, and SEOs publicly pointed to thin, off-topic, traffic-at-all-costs content that drifted beyond HubSpot’s core expertise.
The SEO identity crisis continued as Google dismissed new acronyms like GEO (generative engine optimization) and AEO (answer engine optimization), arguing that good SEO is good GEO, and that the same fundamentals drive AI Overview rankings.
That stance collided with Google’s own admission that search traffic decline is inevitable as AI answers replace clicks, even while traditional search still dominates discovery at a massive scale.
Yet, search behavior is fracturing: users turn to AI for quick answers and to Google for deeper research, pushing brands to optimize for visibility, not just traffic.
Google rapidly expanded AI Mode from an opt-in experiment into a widely available, and possibly soon default, search experience. It added deeper research, agentic actions, personalization, and Gemini 2.5, signaling longer and more complex search behavior.
At the same time, AI Mode exposed major transparency gaps. It initially broke referral tracking and still blends performance data into standard Search Console reports, raising new concerns about visibility, attribution, and what SEO becomes as AI takes on a larger role in search.
Cloudflare CEO Matthew Prince said AI was breaking the web’s search-driven business model. He said Google scraped far more content while sending back much less traffic because of zero-click results. He added that AI companies deepen the imbalance by consuming huge amounts of content with little return to creators, putting original publishing at risk unless the economic model changes.
Statcounter data showed Google’s global search share fell below 90% in October, November, and December 2024, the first time its search share remained under 90% since early 2015. The decline was driven mainly by Asia, alongside a December U.S. dip to 87.39%. Bing, Yandex, and Yahoo captured much of the lost share.
Google tightened its stance on AI-generated content by telling quality raters to give the Lowest ratings to pages where most main content is auto- or AI-generated with little originality or added value. It also expanded its spam definitions to target scaled, low-effort AI use.
At the same time, Google tested AI-generated and AI-summarized search snippets, pointing to a future where AI both judges content more harshly and increasingly controls how that content appears in search.
Analyses from Seer, Ahrefs, Amsive, and BrightEdge all showed the same pattern. Google Search produced more impressions and more AI Overview visibility, but sent fewer clicks. The drop was sharpest on non-branded, informational queries, where AI Overviews pushed classic results down, and CTR fell hard.
The studies also found a winner-take-some dynamic. Brands cited in AI Overviews saw higher paid and organic CTR, while those left out lost ground, showing that AI visibility increasingly drives results.
Google’s removal of the long-standing &num=100 search parameter disrupted SEO data across the industry. It broke rank-tracking tools and coincided with sharp drops in Google Search Console impressions and query counts.
Early analysis showed most sites lost reported visibility, especially beyond Page 1. The change suggested years of inflated metrics from scrapers and a new, possibly more accurate, view of organic performance.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2021/12/web-design-creative-services.jpg?fit=1500%2C600&ssl=16001500http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-12-29 13:00:002025-12-29 13:00:00Top 10 SEO news stories of 2025
OpenAI is laying the groundwork for an advertising business, signaling a potential shift in how ChatGPT and other products could be monetized beyond subscriptions and enterprise deals.
What’s happening. According to reporting from The Information, OpenAI has begun exploring ad formats and partnerships, with early discussions pointing toward ads that could appear within or alongside AI-generated responses. The effort is still in its early stages, but internal conversations suggest ads are becoming a more serious part of OpenAI’s long-term revenue strategy.
Why we care. OpenAI is exploring ads inside AI-generated responses, creating a new, highly contextual channel for reaching users at the moment they seek information. This could put OpenAI in direct competition with Google and Meta, but also raises questions about trust and user engagement. Early adoption could offer a first-mover advantage, while formats and metrics may differ from traditional digital ads. Overall, it’s a potentially transformative new frontier for advertising.
Your customers search everywhere. Make sure your brand shows up.
The SEO toolkit you know, plus the AI visibility data you need.
Start Free Trial
Get started with
Between the lines. OpenAI appears cautious, aiming to avoid disrupting user experience or undermining confidence in its models. Any ad product is likely to be tightly controlled, at least initially, and positioned as helpful or contextually relevant rather than overtly promotional.
The bigger picture. With soaring infrastructure costs and growing pressure to scale revenue, ads could become a key lever for OpenAI — especially as generative AI reshapes how people search for information and discover products.
What to watch. When ads move from internal planning to public testing, how clearly they’re labeled, and whether users accept advertising embedded in AI responses.
Bottom line. OpenAI isn’t rushing ads to market, but the foundations are being laid — and their eventual arrival could reshape both AI products and the digital advertising landscape.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2021/12/web-design-creative-services.jpg?fit=1500%2C600&ssl=16001500http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-12-24 16:18:022025-12-24 16:18:02OpenAI discusses an ad-driven strategy centered on ChatGPT scale and media partnerships
Google reduced the minimum audience size requirement to just 100 active users across all networks and audience types, making remarketing and customer list targeting far more accessible—especially for smaller advertisers.
What’s new. Audience segments with as few as 100 users can now be used across Search, Display, and YouTube, including both remarketing lists and customer lists. The same 100-user threshold now applies for segments to appear in Audience Insights, down from 1,000.
Why we care. Smaller accounts and niche advertisers can now activate audience strategies that were previously out of reach due to size constraints. This change removes a long-standing barrier to personalization, remarketing, and first-party data activation within Google Ads.
What to watch. How advertisers use smaller, more precise segments—and whether performance or privacy safeguards evolve alongside the expanded access.
First seen. This update was first spotted by Web Marketing Consultant, Dario Zannoni, who shared it on LinkedIn.
SEO didn’t stand still in 2025. It didn’t reinvent itself either. It clarified what actually matters. If you followed The SEO Update by Yoast monthly webinars this year, you’ll recognize the pattern. Throughout 2025, our Principal SEOs, Carolyn Shelby and Alex Moss, cut through the noise to explain not just what was changing but why it mattered as AI-powered search reshaped visibility, trust, and performance. If you missed some sessions or want the full picture in one place, this wrap-up is for you. We’re looking back at how SEO evolved over the year, what those changes mean in practice, and what they signal going forward.
Key takeaways
In 2025, SEO shifted its focus from rankings to visibility management, as AI-driven search reshaped priorities
Key developments included the rise of AI Overviews, a shift from clicks to citations, and increased importance of clarity and trust
Brands needed to prioritize structured, credible content that AI systems could easily interpret to remain visible
By December, SEO transformed to retrieval-focused strategies, where success rested on clarity, relevance, and E-E-A-T signals
Overall, 2025 clarified that the fundamentals still matter but emphasized the need for precision in content for AI-driven systems
AI-powered, personalized search accelerated. Zero-click results increased. Brand signals, E-E-A-T, performance, and schema shifted from optimizations to requirements.
SEO expanded from ranking pages to representing trusted brands that machines can understand.
February
Massive AI infrastructure investments. AI Overviews pushed organic results down. Traffic dropped while brand influence and revenue held steady.
SEO outcomes can no longer be measured by traffic alone. Authority and influence matter more than raw clicks.
March
AI Overviews expanded as clicks declined. Brand mentions appeared to play a larger role in AI-driven citation and selection behavior than links alone. Search behavior grew despite fewer referrals.
Visibility fractured across systems. Trust and brand recognition became the differentiators for inclusion.
April
Schema and structure proved essential for AI interpretation. Multimodal and personalized search expanded. Zero-click behavior increased further.
SEO shifted from optimization to interpretation. Clarity and structure determine reuse.
May
Discovery spread beyond Google. AI Overviews reached mass adoption. Citations replaced visits as success signals.
SEO outgrew the SERP. Presence across platforms and AI systems became critical.
June – July
AI Mode became core to search. Ads entered AI answers. Indexing alone no longer offers guaranteed visibility. Reporting lagged behind reality.
Traditional SEO remained necessary but insufficient. Resilience and adaptability became essential.
August
Visibility without value became a real risk. SEO had to tie exposure to outcomes beyond the number of sessions.
Visibility without value became a real risk. SEO had to tie exposure to outcomes beyond sessions.
September
AI Mode neared default status. Legal, licensing, and attribution pressures intensified. Persona-based strategies gained relevance.
Control over visibility is no longer guaranteed. Trust and credibility are the only durable advantages.
October
Search Console data reset expectations. AI citations outweighed rankings. AI search became the destination.
SEO success depends on presence inside AI systems, not just SERP positions.
November
AI Mode became core to search. Ads entered AI answers. Indexing alone is no longer a guarantee of visibility. Reporting lagged behind reality.
Clarity and structure beat scale. Authority decides inclusion.
December
SEO fully shifted to retrieval-based logic. AI systems extracted answers, not pages. E-E-A-T acted as a gatekeeper.
SEO evolved into visibility management for AI-driven search. Precision replaced volume.
January: SEO enters the age of representation
January set the tone for the year. Not through a single disruptive update, but through a clear signal that SEO was moving away from pure rankings toward something broader. The search was becoming more personalized, AI-driven, and selective about which sources it chose to surface. Visibility was no longer guaranteed just because you ranked well.
From the start of the year, it was clear that SEO in 2025 would reward brands that were trusted, technically sound, and easy for machines to understand.
What changed in January
Here are a few clear trends that began to shape how SEO worked in practice:
AI-powered search became more personalized: Search results reflected context more clearly, taking into account location, intent, and behavior. The same query no longer produced the same result for every user
Zero-click searches accelerated: More answers appeared directly in search results, reducing the need to click through, especially for informational and local queries
Brand signals and reviews gained weight: Search leaned more heavily on real-world trust indicators like brand mentions, reviews, and overall reputation
E-E-A-T became harder to ignore: Clear expertise, ownership, and credibility increasingly acted as filters, not just quality guidelines
The role of schema started to shift: Structured data mattered less for visual enhancements and more for helping machines understand content and entities
What to take away from January
January wasn’t about tactics. It was about direction.
SEO started rewarding clarity over cleverness. Brands over pages. Trust over volume. Performance over polish. If search engines were going to summarize, compare, and answer on your behalf, you needed to make it easy for them to understand who you are, what you offer, and why you are credible.
That theme did not fade as the year went on. It became the foundation for everything that followed.
February: scale, money, and AI made the shift unavoidable
If January showed where search was heading, February showed how serious the industry was about getting there. This was the month where AI stopped feeling like a layer on top of search and started looking like the foundation underneath it.
Massive investments, changing SERP layouts, and shifting performance metrics all pointed to the same conclusion. Search was being rebuilt for an AI-first world.
What changed in February
As the month unfolded, the signs became increasingly difficult to ignore.
AI Overviews pushed organic results further down: AI Overviews appeared in a large share of problem-solving queries, favoring authoritative sources and summaries over traditional organic listings
Traffic declined while brand value increased: High-profile examples showed sessions dropping even as revenue grew. Visibility, influence, and brand trust started to matter more than raw sessions
AI referrals began to rise: Referral traffic from AI tools increased, while Google’s overall market share showed early signs of pressure. Discovery started spreading across systems, not just search engines
What to take away from February
February made January’s direction feel permanent.
When AI systems operate at this scale, they change how visibility works. Rankings still mattered, but they no longer told the full story. Authority, brand recognition, and trust increasingly influenced whether content was surfaced, summarized, or ignored.
The takeaway was clear. SEO could no longer be measured only by traffic. It had to be understood in terms of influence, representation, and relevance across an expanding search ecosystem.
March: visibility fractured, trust became the differentiator
By March, the effects of AI-driven search were no longer theoretical. The conversation shifted from how search was changing to who was being affected by it, and why.
This was the month where declining clicks, citation gaps, and publisher pushback made one thing clear. Search visibility was fragmenting across systems, and trust became the deciding factor in who stayed visible.
What changed in March
The developments in March added pressure to trends that had already been forming earlier in the year.
AI Overviews expanded while clicks declined: Studies showed that AI Overviews appeared more frequently, while click-through rates continued to decline. Visibility increasingly stopped at the SERP
Brand mentions mattered more than links alone: Citation patterns across AI platforms varied, but one signal stayed consistent. Brands mentioned frequently and clearly were more likely to surface
Search behavior continued to grow despite fewer clicks: Overall search volume increased year over year, showing that users weren’t searching less; they were just clicking less
AI search struggled with attribution and citations: Many AI-powered results failed to cite sources consistently, reinforcing the need for strong brand recognition rather than reliance on direct referrals
Search experiences became more fragmented: New entry points like Circle to Search and premium AI modes introduced additional layers to discovery, especially among younger users
Structured signals evolved for AI retrieval: Updates to robots meta tags, structured data for return policies, and “sufficient context” signals showed search engines refining how content is selected and grounded
March exposed the tension at the heart of modern SEO.
Search demand was growing, but traditional traffic was shrinking. AI systems were answering more questions, but often without clear attribution. In that environment, being a recognizable, trusted brand mattered more than being the best-optimized page.
The implication was simple. SEO was no longer just about earning clicks. It was about earning inclusion, recognition, and trust across systems that don’t always send users back.
April: machines started deciding how content is interpreted
By April, the focus shifted again. The question was no longer whether AI would shape search, but how machines decide what content means and when to surface it.
After March exposed visibility gaps and attribution issues, April zoomed in on interpretation. How AI systems read, classify, and extract information became central to SEO outcomes.
What changed in April
April brought clarity to how modern search systems process content.
Schema has proven its value beyond rankings: Microsoft has confirmed that schema markup helps large language models understand content. Bing Copilot used structured data to generate clearer, more reliable answers, reinforcing the schema’s role in interpretation rather than visual enhancement
AI-driven search became multimodal: Image-based queries expanded through Google Lens and Gemini, allowing users to search using photos and visuals instead of text alone
AI Overviews expanded during core updates: A noticeable surge in AI Overviews appeared during Google’s March core update, especially in travel, entertainment, and local discovery queries
Clicks declined as summaries improved: AI-generated content summaries reduced the need to click through, accelerating zero-click behavior across informational and decision-based searches
Content structure mattered more than special optimizations: Clear headings that boost readability, lists, and semantic cues helped AI systems extract meaning. There were no shortcuts. Standard SEO best practices carried the weight
What to take away from April
April shifted SEO from optimization to interpretation.
Search engines and AI systems didn’t just look for relevance. They looked for clarity. Content that was well-structured, semantically clear, and grounded in real entities was easier to understand, summarize, and reuse.
The lesson was subtle but important. You didn’t need new tricks for AI search. You needed content that was easier for machines to read and harder to misinterpret.
By May, it was no longer sufficient to discuss how search engines interpret content. The bigger question became where discovery was actually happening.
SEO started expanding beyond Google. Visibility fractured across platforms, AI tools, and ecosystems, forcing brands to think about presence rather than placement.
What changed in May
The month highlighted how search and discovery continued to decentralize.
Search behavior expanded beyond traditional search engines: Around 39% of consumers now use Pinterest as a search engine, with Gen Z leading adoption. Discovery increasingly happened inside platforms, not just through search bars
AI Overviews reached mass adoption: AI Overviews reportedly reached around 1.5 billion users per month and appeared in roughly 13% of searches, with informational queries driving most of that growth
Clicks continued to give way to citations: As AI summaries became more common, being referenced or cited mattered more than driving a visit, especially for top-of-funnel queries
AI-powered search diversified across tools: Chat-based search experiences added shopping, comparison, and personalization features, further shifting discovery away from classic result pages
Economic pressure on content ecosystems increased: Industry voices warned that widespread zero-click answers were starting to weaken the incentives for content creation across the web
May reframed SEO as a visibility problem, not a traffic problem.
When discovery happens across platforms, summaries, and AI systems, success depends on how clearly your content communicates meaning, credibility, and relevance. Rankings still mattered, but they were no longer the primary measure of success.
The message was clear. SEO had outgrown the SERP. Brands that focused on authenticity, semantic clarity, and structured information were better positioned to stay visible wherever search happened next.
By early summer, SEO entered a more uncomfortable phase. Visibility still mattered, but control over how and where content appeared became increasingly limited.
June and July were about adjustment. Search moved closer to AI assistants, ads blended into answers, and traditional SEO signals no longer guaranteed exposure across all search surfaces.
What changed in June and July
This period introduced some of the clearest operational shifts of the year.
AI Mode became a first-class search experience: AI Mode was rolled out more broadly, including incognito use, and began to merge into core search experiences. Search was no longer just results. It was conversation, summaries, and follow-ups
Ads entered AI-generated answers: Google introduced ads inside AI Overviews and began testing them in conversational AI Mode. Visibility now competes not only with other pages, but with monetized responses
Measurement lagged behind reality: Search Console confirmed AI Mode data would be included in performance reports, but without separate filters or APIs. Visibility changed more rapidly than reporting tools could keep pace.
Citations followed platform-specific preferences: Different AI systems favored different sources. Some leaned heavily on encyclopedic content, others on community-driven platforms, reinforcing that one SEO strategy would not fit every system
Most AI-linked pages still ranked well organically: Around 97% of URLs referenced in AI Mode ranked in the top 10 organic results, showing that strong traditional SEO remained a prerequisite, even if it was no longer sufficient
Content had to resist summarization: Leaks and tests showed that some AI tools rarely surfaced links unless live search was triggered. Generic, easily summarized modern content became easier to replace
Infrastructure became an SEO concern again: AI agents increased crawl and request volume, pushing performance, caching, and server readiness back into focus
Search moved beyond text: Voice-based interactions, audio summaries, image-driven queries, and AI-first browsers expanded how users searched and consumed information
What to take away from June and July
This period forced a mindset shift.
SEO could no longer assume that ranking, indexing, or even traffic guaranteed visibility. AI systems decided when to summarize, when to cite, and when to bypass pages entirely. Ads, assistants, and alternative interfaces now often sit between users and websites more frequently than before.
The conclusion was pragmatic. Strong fundamentals still mattered, but they weren’t the finish line. SEO now requires resilience: content that carries authority, resists simplification, loads fast, and stays relevant even when clicks don’t follow.
By the end of July, one thing was clear. SEO wasn’t disappearing. It was operating under new constraints, and the rest of the year would test how well teams adapted to them.
August: the gap between visibility and value widened
By August, SEO teams were staring at a growing disconnect. Visibility was increasing, but traditional outcomes were harder to trace back to it.
This was the month when the mechanics of AI-driven search became more transparent and more uncomfortable.
What changed in August
August surfaced the operational realities behind AI-powered discovery.
Impressions rose while clicks continued to decline: AI Overviews dominated the results, driving exposure without generating traffic. In some cases, conversions still improved, but attribution became harder to prove
The “great decoupling” became measurable: Visibility and performance stopped moving in sync. SEO teams saw growth in impressions even as sessions declined
Zero-click searches accelerated further: No-click behavior climbed toward 69%, reinforcing that many user journeys now ended inside search interfaces
AI traffic stayed small but influential: AI-driven referrals still accounted for under 1% of traffic for most sites, yet they shaped expectations around answers, speed, and convenience
Retrieval logic shifted toward context and intent: New retrieval approaches prioritized meaning, relationships, and query context over keyword matching
It reinforced the reality that SEO could no longer rely on traffic as the primary proof of value. Visibility still mattered, but only when paired with outcomes that could survive reduced clicks and blurred attribution.
The lesson was strategic. SEO needed to connect visibility to conversion, brand lift, or long-term trust, not just sessions. Otherwise, its impact would be increasingly hard to defend.
September: control, attribution, and trust were renegotiated
September pushed the conversation further. It wasn’t just about declining clicks anymore. It was about who controlled discovery, attribution, and access to content.
This was the month where legal, technical, and strategic pressures collided.
What changed in September
September reframed SEO around governance and credibility.
AI Mode moved closer to becoming the default: Search experiences shifted toward AI-driven answers with conversational follow-ups and multimodal inputs
The decline of the open web was acknowledged publicly: Court filings and public statements confirmed what many publishers were already feeling. Traditional web traffic was under structural pressure
Legal scrutiny intensified: High-profile settlements and lawsuits highlighted growing challenges around training data, summaries, and lost revenue
Licensing entered the SEO conversation: New machine-readable licensing approaches emerged as early attempts to restore control and consent
Snippet visibility became a gateway signal: AI tools relied heavily on search snippets for real-time answers, making concise, extractable content more critical
Persona-based strategies gained traction: SEO began shifting from keyword targeting to persona-driven content aligned with how AI systems infer intent
Trust eroded around generic, formulaic, AI writing styles: Formulaic, overly polished AI content raised credibility concerns, reinforcing the need for editorial judgment
Measurement tools lost stability again: Changes to search parameters disrupted rank tracking, reminding teams that SEO reporting would remain volatile
What to take away from September
September forced SEO to grow up again.
Control over visibility, attribution, and content use was no longer guaranteed. Trust, clarity, and credibility became the only durable advantages in an ecosystem shaped by AI intermediaries.
The takeaway was sobering but useful. SEO could still drive value, but only when it is aligned with real user needs, strong brand signals, and content that earned its place in AI-driven answers.
October marked a turning point in how SEO performance needed to be interpreted. The data didn’t just shift. It reset expectations entirely.
This was the month when SEO teams had to accept that AI-powered search was no longer a layer on top of results. It was becoming the place where searches ended.
What changed in October
October brought clarity, even if the numbers looked uncomfortable.
AI Mode reshaped user behavior: Around a third of searches now involve AI agents, with most sessions staying inside AI panels. Clicks became the exception, not the default
AI citations increasingly rivalled rankings: Visibility increasingly depended on whether content was selected, summarized, or cited by AI systems, not where it ranked
Search engines optimized for ideas, not pages: Guidance from search platforms reinforced that AI systems extract concepts and answers, not entire URLs
Metadata lost some direct control: Tests of AI-generated meta descriptions suggested that manual optimization would carry less influence over how content appears
Commerce and search continued to merge: AI-driven shopping experiences expanded, signaling that transactional intent would increasingly be handled inside AI interfaces
What to take away from October
October reframed SEO as presence within AI systems.
Traffic still mattered, but it was no longer the primary outcome. The real question became whether your content appeared at all inside AI-driven answers. Clarity, structure, and extractability replaced traditional ranking gains as the most reliable levers.
From this point on, SEO had to treat AI search as a destination, not just a gateway.
November: structure and credibility decided inclusion
If October reset expectations, November showed what actually worked.
This month narrowed the gap between theory and practice. It became clearer why some content consistently surfaced in AI results, while other content disappeared.
What changed in November
November focused on how AI systems select and trust sources.
Structured content outperformed clever content: Clear headings, predictable formats, and direct answers made it easier for AI systems to extract and reuse information
Schema supported understanding, not visibility alone: Structured data remained valuable, but only when paired with clean, readable on-page content
AI-driven shopping and comparisons accelerated: Product data quality, consistency, and accessibility directly influenced whether brands appeared in AI-assisted decision flows
Citation pools stayed selective: AI systems relied on a relatively small set of trusted sources, reinforcing the importance of brand recognition and authority
Search tooling evolved toward themes, not keywords: Grouped queries and topic-based insights replaced one-keyword performance views
What to take away from November
November made one thing clear. SEO wasn’t about producing more content or optimizing harder. It was about making content easier to understand and harder to ignore.
Clarity beats creativity. Structure beat scale. Authority determined whether content was reused at all.
This month quietly reinforced the fundamentals that would define SEO going forward.
Instead of introducing new disruptions, it clarified what 2025 had been building toward all along. SEO was no longer primarily about ranking pages. It was about enabling retrieval.
What changed in December
The year-end review highlighted the new reality of SEO.
Search systems retrieved answers, not pages: AI-driven search experiences pulled snippets, definitions, and summaries instead of directing users to full articles
Literal language still mattered: Despite advances in understanding, AI systems relied heavily on exact phrasing. Terminology choices directly affected retrieval
Content structure became mandatory: Front-loaded answers, short paragraphs, lists, and clear sections made content usable for AI systems
Relevance replaced ranking as the core signal: Being the clearest and most contextually relevant answer mattered more than traditional ranking factors
E-E-A-T acted as a gatekeeper: Recognized expertise, authorship, and trust signals determined whether content was eligible for reuse
Authority reduced AI errors: Strong credibility signals helped AI systems select more reliable sources and reduced hallucinated answers
What to take away from December
December didn’t declare the end of SEO. It defined its next phase.
SEO matured into visibility management for AI-driven systems. Success depended on clarity, credibility, and structure, not shortcuts or volume. The fundamentals still worked, but only when applied with discipline.
By the end of 2025, the direction was clear. SEO didn’t get smaller. It got more precise.
SEO evolved into visibility management for AI-driven search. Precision replaced volume.
2025 didn’t rewrite SEO. It clarified it.
Search moved from ranking pages to retrieving answers. From rewarding volume to rewarding clarity. From clicks to credibility. And from optimization tricks to systems-level understanding.
The fundamentals still matter. Technical health, helpful content, and strong SEO foundations are non-negotiable. But they are no longer the finish line. What separates visible brands from invisible ones now is how clearly their content can be understood, trusted, and reused by AI-driven search systems.
Going into 2026, the goal isn’t to outsmart search engines. It’s to make your expertise unmistakable. Write for humans, structure for machines, and build authority that holds up even when clicks don’t follow.
SEO didn’t get smaller this year. It got more precise. Stay with us for our 2026 verdict on where search goes next.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-12-24 12:52:512025-12-24 12:52:51The 2025 SEO wrap-up: What we learned about search, content, and trust
I get it, these are uncertain times. Organic traffic is dropping like a rock, and new referral traffic coming in from LLMs like ChatGPT barely scratches the surface of what’s been lost.
The narrative of “traffic is simply coming from a new source” is not accurate. Search and engagement are happening in new ways, but CTRs are dropping significantly across nearly all industries.
It’s no surprise that many in the industry are feeling anxious about the future of SEO and whether AI might eventually render their roles obsolete. Bringing this up with your C-suite team might feel like the last thing you want to do.
But here’s the reality: Now is exactly the time to lean in.
Your leadership team needs to understand what’s happening, and, more importantly, what you’re doing about it.
Use this moment to educate, align expectations, and map out how your search strategy is evolving to meet the new landscape head on. Schedule the meeting. Start the conversation.
I’ll walk you through exactly what to do to maximize the value of this very important meeting.
Don’t avoid leadership — address AI visibility head-on
No, I’m not going to tell you to picture your leadership team in their underwear. That won’t make the conversation easier, it’ll just make it awkward.
What will help is showing up prepared to lead the conversation.
Your customers search everywhere. Make sure your brand shows up.
The SEO toolkit you know, plus the AI visibility data you need.
Start Free Trial
Get started with
Set the tone from the start. Your leadership team will already respect the fact that you’re raising this issue before they assign someone to investigate it.
Use this opportunity to guide the discussion and provide clarity, not excuses. This isn’t the time to sugarcoat or downplay what’s happening.
Let’s break down the key points to bring to leadership to provide clarity.
Why SEO is down and how that impacts business
This is your opportunity to lead with facts, not fear. Give an honest recap of the current state of the industry and how it’s affecting your business.
To start, here are a few critical events that may help explain shifts in performance:
Tools like ChatGPT, Gemini, and Perplexity are changing user behavior and pulling searches away from Google entirely.
Google has since rolled out AI Overviews (AIOs), which are appearing in more and more SERPs and driving fewer clicks to third-party sites. (Reports of -61% reduction in organic CTR have been reported).
LLMs are sending some traffic, but it’s a drop in the bucket compared to what’s been lost from traditional search.
Bing launched AI-powered search summaries, but the impact was limited due to its smaller market share.
Next, present a clear, data-driven overview of what’s changed at your company and how it’s already affecting your business. If organic traffic is down 30%, own it, and if revenue has dipped as well, own that too.
Keep the conversation grounded in measurable outcomes and alignment with company goals. And confirm in advance with your analytics team that data you are citing (in addition to LLM visibility metrics you are collecting) are accurate.
Here’s data that needs to be shared.
Discuss revenue, leads (or actions marked as key events), and organic traffic data over time, ideally including year-over-year numbers.
These numbers tie the discussion directly to business impact instead of rankings or other vanity metrics. Year-over-year views help distinguish seasonality and industry trends from real performance drops. Identifying these allows leadership to quickly understand when performance went down vs. a soft market (or shift to a new search ecosystem).
Export and review keywords you’ve been tracking. This is valuable for Google and Bing, and additional insights from LLM rank tracking can add more context.
No, I’m not going against my long standing take that rankings shouldn’t be used as a performance metric on their own. However, in situations like these, rankings are incredibly important to understand if the decrease in traffic is purely lost rankings, lost demand, or shifts in how people search.
Export click/impression and CTR data in Google Search Console and Bing Webmaster Tools. Isolate queries/URLs that saw a CTR decrease and determine if those SERPs are now displaying AIOs.
This further demonstrates when performance is truly down or if everyone playing the game has been impacted. If the pages that saw the biggest dips in clicks also display AI overviews, then the impact is likely very similar for your competitors as well. Just another valuable piece of the puzzle.
Once you deliver the current state of the business, questions will follow. Don’t wait to be asked, own the narrative. Explain the broader context, industry-wide shifts, and emerging technologies behind these changes. A few opportunities to consider:
Pull traffic estimates and keyword ranking reports for your top competitors. Are they seeing similar results?
Review Google Trends and Exploding Topics to identify increasing (or decreasing) demand for topics/products within your industry.
Leverage new AI visibility technology/reports to show your brand’s visibility where the conversation/research is happening (LLMs).
Remember, this isn’t about assigning blame. It’s about showing you understand the change in landscape and how it’s impacting overall performance.
What we’ve learned so far and where we’re going
This is the moment to show leadership that you are not just diagnosing a problem, you are actively working toward a solution. They might not love every answer, but they will respect that you are thinking three steps ahead.
Make it clear that while the rules are changing, your team is already adapting to win in the next era of search. Then be explicit about what you need from them, whether that’s budget, headcount, data support, or cross-functional alignment, so you can actually execute the plan instead of just presenting the problem.
Here are a few ideas to communicate the next plan of attack.
We are working to increase our brand’s presence outside of traditional search, focusing heavily on AI-generated answers and emerging discovery platforms.
That includes tracking which questions matter most to our buyers, understanding where our brand appears today, and prioritizing content, PR, and partnerships to increase our odds of being named in those answers.
The goal is simple: If people are getting answers without clicking, our brand still needs to show up in the answer. This is done by repetition and consistency in our brand mentions/citations across the web.
We are rethinking content strategy around entities and topics, not just keywords and rankings.
LLMs reward brands that have deep, consistent coverage of a topic and clear signals of expertise. That affects what we publish, how we structure content, and how we collaborate with PR, product, and subject matter experts to build authority over time. This is the 2.0 version of “SEO content” and it won’t be easy, but the results will be worth it.
We are investing in visibility measurement across both traditional and non-traditional search channels.
Google organic traffic is no longer the single source of truth. We are building reporting that accounts for AI surfaces, social discovery, referral ecosystems, and even offline demand, so the broader team sees the full picture instead of assuming “SEO is down, therefore demand is down.” This helps quantify the broader shift in search ecosystems.
AI Overviews are a permanent shift, not a test.
This means resetting traffic baselines, forecasts, and goals to reflect fewer clicks from classic blue links within the SERP. We are not planning our pipeline in the hope that Google turns AI Overviews off, we are planning for a world where this is the new normal.
Some version of “AI Mode” will likely become Google’s default experience in 2026.
If more searches are answered directly in Google’s interface, fewer visitors will hit our site. That changes how many leads or sales we can expect from SEO alone, and it will force us to rethink everything, including budgeting and how we attribute performance across channels.
How we’ll be proactive and adapt to the new search landscape
You’ve explained what’s happening, why it’s happening, and how your team is adapting. Now, make it clear to leadership that to succeed in this shifting landscape, it can’t be done in isolation. You’ll need alignment, resources, and ongoing support.
Use this opportunity to preemptively answer questions like “What do you need from us?” and to shape the path forward. Leaders like nothing more than an actionable plan that they simply have to bless to get done.
Here are some critical needs to outline.
Search success in the AI era looks different, is measured differently than we are used to, and will take time to optimize.
We should agree up front on realistic timeframes, what leading indicators we will track, and how often we will report back. Rankings, traffic, and last-click revenue will not always move neatly in sync, so leadership needs to be comfortable with a period where we are learning and recalibrating, not just chasing last year’s dashboards.
Executive buy-in is needed to prioritize long-term brand-building alongside short-term performance metrics.
This means leadership agrees that some SEO and content initiatives will not pay off in this quarter’s reporting but are required to keep the brand visible in search and AI-driven experiences over the next 12 to 24 months. It also means updating KPIs so the team is not punished for investing in assets that compound over time instead of quick, last-click wins.
Budget flexibility to invest in experimental channels, new content formats, and tools that help track AI visibility.
A portion of the marketing budget will need to be earmarked for testing, for example: new AI visibility tools, structured data implementations, interactive content, and partnerships that increase the odds of being cited in AI answers. The goal is to learn fast, kill what does not work, and scale what does.
Cross-functional collaboration with analytics, product, PR, and content teams needs to happen to shift how we measure and execute organic growth.
SEO can no longer operate in a silo. We need analytics to help us build new dashboards that track visibility and assisted impact, PR to prioritize stories and placements that feed both search and AI systems, and product and content teams to align roadmaps with the topics and entities that matter most. Without that alignment, we end up with fragmented efforts and noisy data that no one trusts.
This is your moment to lead the AI visibility discussion
You’re not just reacting to change but guiding your organization through it. AI and LLMs are rewriting how people search, discover, and click. This isn’t the time to panic, let alone support the “organic search is dead” rumor. It means the game has changed, and good businesses aren’t afraid. They adapt.
Part of that strategy is ongoing monitoring. One-time pitches for buy-in are great, but all marketing efforts need to be measured. Set a regular cadence—for example, a monthly AI visibility update metric alongside your “normal” SEO KPIs.
As AI and LLMs evolve, you can leverage the data you’ve measured to brief leadership on what has changed and how you have adapted to the situation.
See the complete picture of your search visibility.
Track, optimize, and win in Google and AI search from one platform.
Start Free Trial
Get started with
By getting ahead of the conversation, grounding your message in data, and proposing a realistic path forward, you’re showing exactly the kind of strategic thinking that executives value.
This is no longer only about SEO, it’s about future-proofing how your business earns visibility, trust, and traffic in a radically new environment. It doesn’t matter if that happens on Google, ChatGPT, Reddit, or anywhere else. What’s important is being visible in the spaces where your customers are hanging out.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2021/12/web-design-creative-services.jpg?fit=1500%2C600&ssl=16001500http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-12-23 18:11:432025-12-23 18:11:43AI’s impact on search isn’t a secret (How to talk to execs about the new era of search)
Most business owners assume that if an ad is approved by Google or Meta, it is safe.
The thinking is simple: trillion-dollar platforms with sophisticated compliance systems would not allow ads that expose advertisers to legal risk.
That assumption is wrong, and it is one of the most dangerous mistakes an advertiser can make.
The digital advertising market operates on a legal double standard.
A federal law known as Section 230 shields platforms from liability for third-party content, while strict liability places responsibility squarely on the advertiser.
Even agencies have a built-in defense. They can argue that they relied on your data or instructions. You can’t.
In this system, you are operating in a hostile environment.
The landlord (the platform) is immune.
Bad tenants (scammers) inflate the cost of participation.
And when something goes wrong, regulators come after you, the responsible advertiser, not the platform, and often not even the agency that built the ad.
Here is what you need to know to protect your business.
Note:This article was sparked by a recent LinkedIn post from Vanessa Otero regarding Meta’s revenue from “high-risk” ads. Her insights and comments in the post about the misalignment between platform profit and user safety prompted this in-depth examination of the legal and economic mechanisms that enable such a system.
The core danger: Strict liability explained
While the strict liability standard is specific to U.S. law (FTC), the economic fallout of this system affects anyone buying ads on U.S.-based platforms.
Before we discuss the platforms, it is essential to understand your own legal standing.
In the eyes of the FTC and state regulators, advertisers are generally held to a standard of strict liability.
What this means: If your ad makes a deceptive claim, you are liable. That’s it.
Intent doesn’t matter: You can’t say, “I didn’t mean to mislead anyone.”
Ignorance doesn’t matter: You can’t say, “I didn’t know the claim was false.”
Delegation doesn’t matter: You can’t say, “My agency wrote it,” or “ChatGPT wrote it.”
The law views the business owner as the “principal” beneficiary of the ad.
You have a non-delegable duty to ensure your advertising is truthful.
Even if an agency writes unauthorized copy that violates the law, regulators often fine the business owner first because you are the one profiting from the sale.
You can try to sue your agency later to get your money back, but that is a separate battle you have to fund yourself.
The unfair shield: Why the platform doesn’t care
If you are strictly liable, why doesn’t the platform help you stay compliant? Because they don’t have to.
Section 230 of the Communications Decency Act declares that “interactive computer services” (platforms) are not treated as the publisher of third-party content.
The original intent: This law was passed in 1996 to allow the internet to scale, ensuring that a website wouldn’t be sued every time a user posted a comment. It was designed to protect free speech and innovation.
The modern reality: Today, that shield protects a business model. Courts have ruled that even if platforms profit from illegal content, they are generally not liable unless they actively contribute to creating the illegality.
The consequence: This creates a “moral hazard.” Because the platform faces no legal risk for the content of your ads, it has no financial incentive to build perfect compliance tools. Their moderation AI is built to protect the platform’s brand safety, not your legal safety.
The liability ladder: Where you stand
To understand how exposed you are, look at the legal hierarchy of the three main players in any ad campaign:
The platform (Google/Meta)
Legal status: Immune.
They accept your money to run the ad. Courts have ruled that providing “neutral tools” like keyword suggestions does not make the platform liable for the fraud that ensues.
If the FTC sues, they point to Section 230 and walk away.
The agency (The creator)
Legal status: Negligence standard.
If your agency writes a false ad, they are typically only liable if regulators prove they “knew or should have known” it was false.
They can argue they relied on your product data in good faith.
You (The business owner)
Legal status: Strict liability.
You are the end of the line.
You can’t pass the buck to the platform (immune) or easily to the agency (negligence defense).
If the ad is false, you pay the fine.
The hostile environment: Paying to bid against ‘ghosts’
The situation gets worse.
Because platforms are immune, they allow “high-risk” actors into the auction that legitimate businesses, like yours, have to compete against.
A recent Reuters investigation revealed that Meta internally projected roughly 10% of its ad revenue (approximately $16 billion) would come from “integrity risks”:
Scams.
Frauds.
Banned goods.
Worse, internal documents reveal that when the platform’s AI suspects an ad is a scam (but isn’t “95% certain”), it often fails to ban the advertiser.
Instead, it charges them a “penalty bid,” a premium price to enter the auction.
You are bidding against scammers who have deep illicit profit margins because they don’t ship real products (zero cost of goods sold).
This allows them to bid higher, artificially inflating the cost per click (CPC) for every legitimate business owner.
You are paying a fraud tax just to get your ad seen.
Because the platform is no longer a neutral host but is vouching for the business (“Guaranteed”), regulators can argue they have stepped out from behind the Section 230 shield.
By clicking “Auto-apply,” you are effectively signing a blank check for a robot to write legal promises on your behalf.
Risk reality check: Who actually gets investigated?
While strict liability is the law, enforcement is not random. The FTC and State Attorneys General have limited resources, so they prioritize based on harm and scale.
If you operate in dietary supplements (i.e., “nutra”), fintech (crypto and loans), or business opportunity offers, your risk is extreme. These industries trigger the most consumer complaints and the swiftest investigations.
If you are an HVAC tech or a local florist, you are unlikely to face an FTC probe unless you are engaging in massive fraud (e.g., fake reviews at scale). However, you are still vulnerable to competitor lawsuits and local consumer protection acts.
Investigations rarely start from a random audit. They start from consumer complaints (to the BBB or attorney generals) or viral attention. If your aggressive ad goes viral for the wrong reasons, the regulators will see it.
International intricacies
It is vital to remember that Section 230 is a U.S. anomaly.
If you advertise globally, you’re playing by a different set of rules.
The European Union (DSA): The Digital Services Act forces platforms to mitigate “systemic risks.” If they fail to police scams, they face fines of up to 6% of global turnover.
The United Kingdom (Online Safety Act): The UK creates a “duty of care.” Senior managers at tech companies can face criminal liability for failing to prevent fraud.
Canada (Competition Bureau): Canadian regulators are increasingly aggressive on “drip pricing” and misleading digital claims, without a Section 230 equivalent to shield the platforms.
The “Brussels Effect”: Because platforms want to avoid EU fines, they often apply their strictest global policies to your U.S. account. You may be getting flagged in Texas because of a law written in Belgium.
The advertiser’s survival guide
Knowing the deck is stacked, how do you protect your business?
Adopt a ‘zero trust’ policy
Never hit “publish” on an auto-generated asset without human eyes on it first.
If you use an agency, require them to send you a “substantiation PDF” once a quarter that links every claim in your top ads to a specific piece of proof (e.g., a lab report, a customer review, or a supply chain document).
The substantiation file
For every claim you make (“Fastest shipping,” “Best rated,” “Loses 10lbs”), keep a PDF folder with the proof dated before the ad went live.
This is your only shield against strict liability.
Audit your ‘auto-apply’ settings
Go into your ad accounts today.
Turn off any setting that allows the platform to automatically rewrite your text or generate new assets without your manual review.
Efficiency is not worth the liability.
Watch the legislation
Lawmakers are actively debating the SAFE TECH Act, which would carve out paid advertising from Section 230.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/12/Why-ad-approval-is-not-legal-protection-Mf1Pt4.webp?fit=1920%2C1080&ssl=110801920http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-12-23 15:00:002025-12-23 15:00:00Why ad approval is not legal protection
Google expanded Demand Gen channel controls to include Google Maps, giving advertisers a new way to reach users with intent-driven placements and far more control over where Demand Gen ads appear.
What’s new. Advertisers can now select Google Maps as a channel within Demand Gen campaigns. The option can be used alongside other channels in a mixed setup or on its own to create Maps-only campaigns.
Why we care. This update unlocks a powerful, location-focused surface inside Demand Gen, allowing advertisers to tailor campaigns to high-intent moments such as local discovery and navigation. It also marks a meaningful step toward finer channel control in what has traditionally been a more automated campaign type.
Response. Advertisers are very excited by this update. CEO of AdSquire Anthony Higman has been waiting for this for decades:
Google Ads Specialist Thomas Eccel, who shared the update on LinkedIn said: “This is very big news and shake up things quite a lot!”
Between the lines. Google continues to respond to advertiser pressure for greater transparency and control, gradually breaking Demand Gen into more modular, selectable distribution channels.
What to watch. How Maps placements perform compared to YouTube, Discover, and Gmail—and whether Google expands reporting or optimization tools specifically for Maps inventory.
First seen. This update was first spotted by Search Marketing Specialist Francesca Poles, when she shared the update on LinkedIn
Bottom line. Adding Google Maps to Demand Gen channel controls is a significant shift that gives advertisers new strategic flexibility and the option to build fully location-centric campaigns.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/12/Screenshot-2025-12-23-at-14.29.48-8lnVvZ.webp?fit=558%2C447&ssl=1447558http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-12-23 14:56:142025-12-23 14:56:14Google adds Maps to Demand Gen channel controls
