It’s halftime.
The first half of 2025 brought major shakeups in SEO, AI, and organic growth – and it’s time for a reality check.
Traffic is down, revenue is … complicated, and large language models (LLMs) are no longer fringe.
Publishers are panicking, and SEO teams are reevaluating how they measure success.
And it’s not just the tech shifting; it’s the economy around it. The DOJ’s antitrust case against Google could reshape the playing field before Q4 even begins.
In today’s Memo, I’m unpacking the state of organic growth at the midpoint of 2025:
- How AI Overviews and AI Mode are eating clicks, and what that means for TOFU, MOFU, and BOFU content.
- Why publishers are suing Google and preparing for zero traffic.
- What’s really happening with tech layoffs and job transformation.
- How we measure LLM visibility today, and where that’s headed.
- What to expect next in organic growth, search, and monetization.
Plus, premium subscribers will receive my scorecard that will help evaluate whether the team is adapting effectively to the AI landscape.
Let’s take stock of where we are, and what comes next.
Boost your skills with Growth Memo’s weekly expert insights. Subscribe for free!
AI Is Cutting Flesh
AI Overviews (AIOs) looked “interesting” to marketers in 2024 and “devastating” in 2025.
The traffic loss impact ranges from 15% to 45% declines, from my own observations.
Bottom-line metrics across the industry range from “traffic down, revenue up” to “traffic down, revenue down.”
In February, I wrote in The Impact of AI Overviews that mostly the top of the funnel (TOFU) queries were impacted:
Every study I looked at confirmed that the majority of AI Overviews show up for informational-intent keywords like questions.
Shortly after, in March 2025, Google nullified that theory by dialing up the number of AIOs way beyond the top of the funnel.
Ever since, U.S. companies have experienced a strong (negative) impact, and I’m hearing the phrase “SEO is dead” more often from leaders.
Between 13 and 19% of keywords show AI Overviews, according to Semrush and seoClarity, but I assume the actual number is much higher because searchers use much longer prompts. (Prompts that most tools don’t track.) [1, 2]
I expect organic traffic to keep dropping as the year moves forward.
In theAIO Usability study I published in May, only a small fraction of clicks still came through to websites.
It wouldn’t surprise me if 70% of the organic traffic that sites earned in 2024 is gone by 2026, leaving just 30% of that organic traffic behind.
Scary? Yes. But traffic is just a means.
The same study also shows that 80% of searchers still lean on organic results to complete their search journeys.
So, I still feel optimistic about the value of organic search in the long term.
There are two questions top of mind for me at the moment:
- If AIOs really only impact the top of the funnel, then why are revenue numbers down?
- At which point is the decline going to level off?
In my view, either:
- AIOs are really mostly TOFU queries. In that case, TOFU content always had more impact on the bottom line than we were able to prove, and we can expect the traffic decline to level off.
- Or AIOs impact way more than MOFU and BOFU queries as well (which is what I think), and we’re in for a long decline of traffic. If true, I expect revenue that’s attributed to organic search to decline at a lower rate, or not at all for certain companies, since purchase intent doesn’t just go away. Therefore, revenue results would relate more to our ability to influence purchase intent.
With one exception.
Publishers Are Struggling
The whole internet is trying to figure out whether the value of showing up in LLMs (ChatGPT, Gemini, AI Mode, AI Overviews, etc.) is worth more than the loss in traffic.
But without a doubt, publishers and affiliates are the group that gets hit the hardest due to their reliance on ad impressions and link clicks.
No one needs traffic as much as publishers.
The consequence? Leading publishers and news sites will conduct layoffs and assume that Google traffic will go to zero at some point.
At a companywide meeting earlier this year, Nicholas Thompson, chief executive of the Atlantic, said the publication should assume traffic from Google would drop toward zero and the company needed to evolve its business model. [3]
Publishers in the EU have banded together and filed an antitrust complaint against Google for its launch and the impact of AI Overviews with the European Commission. [4]
Publishers using Google Search do not have the option to opt out from their material being ingested for Google’s AI large language model training and/or from being crawled for summaries, without losing their ability to appear in Google’s general search results page.
I caught up with Chris Dicker, who leads one of the co-signatories in the DMA complaint against Google, the Independent Publishers Alliance:
Kevin: What’s your role in the lawsuit against Google?
Chris: The Independent Publishers Alliance is one of the co-signatories on the complaint. I am helping lead this from the Alliance side.
Kevin: What would be an outcome, i.e., an action by Google, that would be satisfactory?
Chris: We are only asking for what we deem to be fair, which is for a sustainable ecosystem.
Whether that is payment for use of content or for Google to start to substantially reduce the zero-click searches, which have gotten significantly worse since the launch of AIOs.
Kevin: Can LLMs (ChatGPT & Co) provide some remedy against the traffic drop from Google?
Chris: Not for publishers at the moment, no. They don’t have scale or the want to send traffic anywhere else. The current CTR’s we are seeing and that are being reported from publishers are tiny.
OpenAI’s scrape to human visit is 179:1, compared with Perplexity’s 369:1 and Anthropic’s 8692:1 (stats from Tollbit’s State of bots Q1 2025).
For perspective, Bing’s is 11:1. I know there are reports that the traffic from LLMs is “better quality,” but not on the metrics that would help publishers or content creators.
It is very much the opposite: Bounce rate is higher; pages per session and per visit are also both considerably down for AI search traffic compared to organic search.
Kevin: What are the consequences of Google’s AI Overviews on independent publishers so far? Can you quantify the impact?
Chris: It’s significant and something that has been extrapolated even since April this year. There are sites that are seeing traffic drops of up to 70% since April.
Publishers have no choice but to cut costs and, unfortunately, that also means job losses.
In the last year, we have had numerous members who, unfortunately, haven’t been able to weather the storm and have ceased publishing altogether, and these are respected sites that were well established over the last 10 years, if not longer.
Kevin: Do you know of publishers that are able to dampen the negative impact from AI Overviews in some ways? If so, what are they doing?
Chris: Nearly every publisher I speak to is actively diversifying away from Google.
It feels inevitable that we’ll see a mass blocking of Googlebot at some point, something that would have been inconceivable just 12 months ago.
If your business model still relies on search traffic, whether from traditional search or AI-powered results, it’s time to rethink – and fast.
More publishers are now focusing on direct audience relationships through newsletters, forums, podcasts, and similar channels.
Platforms like Substack offer an interesting model, though I’m not convinced their approach fully suits publishers just yet.
Beyond monetizing websites and content, many publishers are also developing in-house creative, social, or AI agencies. After all, these businesses have spent years engaging and inspiring audiences.
Helping advertisers tap into that expertise feels like a natural next step.
Besides the fact that the open web and critical societal instances are fading away, from a purely practical standpoint, there are also fewer publishers to amplify content for other businesses.
And yet, I believe we haven’t seen the full extent to which Google Search will change from sending traffic to answering questions directly.
AI Mode Is Sitting On The Bench, But It Seems Ready
At a recent event I attended, a Google representative mentioned that Sundar Pichai sees AI Mode as the default search experience in the next two to three years, with searchers being able to switch to classic search results if they want to – assuming users like AI Mode.
And that seems to be the case: According to a (small) survey done by Oppenheimer & Co., 82% of searchers find AI Mode more helpful than Google Search, while 75% find it more helpful than ChatGPT (I wonder why). [5]
Nothing shows fear more than copying a challenger’s user interface and abandoning the cash machine that worked for 20 years.
AI Mode is basically ChatGPT with a Google logo. Google follows the Meta playbook, which fenced in Snapchat’s and TikTok’s growth by copying their core features.
And most alarmingly for search marketers, AI Mode eats clicks for breakfast.
Research by iPullrank found that “4.5% of AI Mode Sessions result in a click.”[6]
A click. As in one!
But Google cannot afford to lose the investor narrative.
I personally believe that AI Mode won’t launch before Google has figured out the monetization model. And I predict that searchers will see way fewer ads but much better ones, and displayed at a better time.
Due to the conversational interface and longer prompts, Google should not only have more context about what users really want, but they would also be able to better estimate when is the best time to show an ad during the chat conversation.
As a result, I expect CPCs will skyrocket, but CPAs will become more efficient.
AEO/GEO/LLMO: Too Many Buzzwords But Not Enough Differentiation
Between AI Mode, AI Overviews, and ChatGPT stands this important question:
How much can we influence answers, and how different is that job from what we’ve done in SEO over the last two decades?
It’s simple. The tactics are mostly the same, but the ecosystem changes:
1. Longer prompts: The average prompt is 23 words long compared to 4.2 for classic Google Search. [7]
The rich detail users provide about their intent hits a content gap that’s tuned for shorthead keywords on the other side of the marketplace.
As a result, I see hyper-specialized content that’s fine-tuned for specific personas (see How to Optimize for Topics) in our present and future.
2. SEO winners are not AI winners: If SEO was enough and there was nothing else we needed to do “for AI,” then why aren’t the sites that are most visible in Search the same ones that are visible in LLMs?
In Is GEO/AEO the same as SEO?, I found that the lists differ greatly in most verticals. Only highly consolidated spaces with a few winners, like CRM software, have identical winners across both modalities.
3. New intent: Generative: Semrush and Profound came to the conclusion that ~30-70% of intent on LLMs is “generative,” meaning users want to accomplish tasks right then and there. [8]
What’s often missed is that while performing an action, e.g., generating an image, the intent can quickly flip to informational or transactional, e.g., learn more about the topic you want to generate the image about or buy icon license.
Since experiences are conversational and more continuous, we need to update our model of intent. It doesn’t happen in isolation (think: one session), but several intents can occur during the same session (informational → generative → transactional → informational → etc.).
My opinion: It’s too soon to coin a term.
Will we switch from Answer Engine Optimization to Agentic Engine Optimization when we enter the Agentic AI age? AI has evolved at a rocket pace over the last 2.5 years, and I don’t expect it will slow down soon.
LLMs Are No Longer Fringe
In 2025, LLMs reached the mainstream. We’re not talking about a fringe platform anymore: ChatGPT supposedly receives 2.5 billion prompts a day.
With Google seeing over 5 trillion searches per year, you could say ChatGPT has reached about 17.8% of Google’s volume.
Keep in mind that a lot of prompts are not searches on ChatGPT, and then the comparison becomes weaker (until Google rolls AI Mode out broadly). [9]
Important to note is that LLMs rely on different citation sources to varying degrees. [10]
Profound saw in 30 million citations that ChatGPT, AIOs, and Perplexity rely on different citation sources:
- ChatGPT cites Wikipedia almost 50% of the time, followed by citing Reddit at 11.3% and Forbes at 6.8%.
- AI Overviews cite Reddit 21% of the time, followed by 18.8% for YouTube, 14.3% for Quora, and 13% for LinkedIn.
- Perplexity cites Reddit almost 50% of the time, YouTube at 13.9% of the time, and Gartner at 7%.
We know that investing time and resources into non-Google platforms is critical to building trust and visibility across all platforms.
But now we know that the mix of platform investment depends on where you want to build visibility.
Reddit seems to provide universal impact, which makes sense given their licensing deals with OpenAI and Google, but YouTube, Quora, and review platforms don’t show the same potential for gaining citations on all LLMs.
Time also matters. AirOps found that 95% of pages cited in ChatGPT are less than 10 months old. [11]
A big reason for this is the training data cutoff for LLMs. New models are still trained on large corpi of data (remember the Google Dance?).
Anything newer than the time of training needs to come from the web. As a result, keeping content fresh and continuously iterating seems like a path to AI visibility to me. Even adding the current year to the URL (and meta-title) seems like a good idea. [12]
A study by Apple, which I covered in the Growth Intelligence Brief, raises a question we might all have at the tip of our tongue: Are LLMs overhyped? [13]
The answer: It depends … on the complexity of the task:
- Simple problems: Models often find correct solutions early but wastefully continue exploring incorrect ones (“overthinking”).
- Moderate complexity: Models explore many incorrect solutions before finding correct ones.
- High complexity: Models fail to generate any correct solutions.
LLMs are smart but still struggle with complex tasks. Good news for tech workers … right?
And here’s another thing: With the increase of LLM use and adoption, how will we measure success for our optimization efforts?
I ran a survey of Growth Memo in June, and it’s clear our industry hasn’t really nailed how we measure the LLM visibility of our brands.
Out of those who responded, about 30% are using traditional SEO tools to measure LLM visibility, 26% are using Google Analytics 4 traffic signals, and a whopping 21% aren’t measuring yet and need help determining how.
And the biggest surprise is this: Overwhelmingly, we don’t trust our LLM visibility measurements.
Close to 80% of survey respondents don’t believe the way they are measuring LLM visibility is accurate.
A big topic in the whole LLM conversation is, of course, whether AI replaces white collar workers or not.
I’m including this discussion in my halftime report because I’m seeing a growing number of in-house experts who are afraid to be replaced.
Amazon’s CEO, Andy Jassy, wrote a public memo, saying the company would need fewer people because of AI (bolded text is mine):
“As we roll out more Generative AI and agents, it should change the way our work is done. We will need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs. It’s hard to know exactly where this nets out over time, but in the next few years, we expect that this will reduce our total corporate workforce as we get efficiency gains from using AI extensively across the company.” [14]
Amazon has cut +27,000 jobs between 2022 and 2023, but has never had more employees at the end of 2024, except for at the end of 2021 by a small margin. [15]
Other tech companies pulled even:
- Salesforce’s CEO, Marc Benioff, says that 30-50% of the work at Salesforce is done by AI. [16] Salesforce eliminated ~1,000 roles this year.
- Klarna’s CEO first announced that AI is doing the work of 700 customer service agents and fired about 2,000 employees, but then backtracked and rehired humans. [17]
- Microsoft cut 15,000 jobs in 2025. CEO Satya Nadella said AI writes ~30% of new code in some projects.
- Meta laid off 3,600 employees in 2025, with Mark Zuckerberg saying AI could be ready to be a mid-level engineer this year.
But is AI really replacing white collar workers, or is it used for good PR?
Layoff tracker, layoffs.fyi, shows that the number of companies and employees laid off is not growing since the pandemic.
A jobs report by CompTIA shows that while tech employment is slightly down between June 2023 and June 2025…[18]
…the number of job openings with AI skills far outpaces the number of listings for all roles.
In other words, “AI layoffs” seem more PR play or justification for job cuts.
But upskilling with AI is critical.
Google Lawsuit Rushes Toward A Final Decision On Labor Day
The landmark lawsuit against Google for being an online search monopoly concludes by Labor Day (September 1). The DoJ asks for:
- A mandatory divestiture of Chrome within a specified timeframe.
- A five-year prohibition on Google owning any browser.
- Termination of exclusive default agreements.
- Extensive data sharing requirements.
- The right to seek Android divestiture if behavioral remedies prove insufficient.
Google, on the other hand, agrees to end exclusive agreements, so we know Google and Apple will divorce, but opposes a Chrome divestiture and data sharing mandates.
The remedy ruling could have significant implications on the AI race, and where marketers should place their money.
For example, a Chrome divestiture could significantly set Google back, as OpenAI and Perplexity launch their own browsers. It would also mean a material loss in user behavior data and agentic AI capabilities.
Losing the exclusive agreement with Apple could also mean that more users set other browsers than Chrome as default, if they can provide a strong benefit.
However, I personally think the most realistic outcome is a forced end to exclusive agreements and would be shocked to see a Chrome divestiture.
For context:
- The Department of Justice has achieved two landmark antitrust victories against Google in 2024-2025, with federal judges ruling the tech giant operates illegal monopolies in both online search and digital advertising technology.
- Both cases have now advanced to remedy phases where courts will determine whether to break up parts of Google’s business, representing the most aggressive government intervention in Big Tech since the Microsoft case 25 years ago.
Outlook For H2
The second half of 2025 will likely be defined by adaptation rather than resistance.
Companies that succeed will be those that foster trust beyond Google, build direct audience relationships, and upskill teams in AI.
Here’s what I expect for the second half of the year:
Accelerating Traffic Decline
- Organic traffic losses will likely intensify as Google expands AI Overviews.
- Publishers should prepare for further 20-30% traffic declines.
- The “new normal” of 30% of historical traffic by 2026 could arrive sooner than expected.
AI Mode Launch
- Google will likely roll out AI Mode more broadly, but cautiously.
- Expect a heavy focus on monetization testing before wide release.
- Watch for new ad formats optimized for conversational search.
Publisher Adaptation
- More publishers will actively block Googlebot.
- Increased focus on direct revenue streams (newsletters, memberships).
- Potential consolidation as smaller publishers struggle to survive.
Measurement Evolution
- New tools specifically for measuring LLM visibility will emerge.
- Industry will start standardizing on key metrics for AI performance.
- Greater emphasis on revenue vs. traffic as success metrics.
Market Restructuring
- DoJ ruling could reshape the search landscape.
- Expect new search entrants to gain traction.
- Browser wars may reignite with AI-native options.
Featured Image: Paulo Bobita/Search Engine Journal
