OpenAI Quietly Adds Shopify As A Shopping Search Partner via @sejournal, @martinibuster

OpenAI has quietly added Shopify as a third-party search partner to help power their shopping search, which shows shopping-rich results. The addition of Shopify was not formally announced, but quietly tucked into OpenAI ChatGPT search documentation.

Shopify Is An OpenAI Search Partner

Aleyda Solís (LinkedIn profile) recently noticed that OpenAI had updated their Search documentation to add Shopify to the list of third party search providers.

She posted:

“Ecommerce sites: I’ve found that Shopify is listed along with Bing as a ChatGPT third-party search provider! OpenAI added Shopify along with Bing as a third-party search provider in their ChatGPT Search documentation on May 15, 2025; a couple of weeks after their enhanced shopping experience was announced on April 28.”

OpenAI Is Showing Merchants From Multiple Platforms

OpenAI shopping search is returning results from a variety of platforms. For example, a search for hunting dog supplies returns sites hosted on Shopify but also Turbify (formerly Yahoo Stores)

Screenshot Showing Origin Of OpenAI Shopping Rich Results

The rich results with images were sourced from Shopify and Amazon merchants for this specific query.

At least one of the shopping results listed in the Recommended Sellers is a merchant hosted on the Turbify ecommerce platform:

Screenshot Of OpenAI Recommended Retailers With Gun Dog Supply, Hosted On Turbify Platform

OpenAI Shopping Features

OpenAI recently rolled out shopping features for ChatGPT Search. Products are listed like search results and sometimes as rich results with images and other shopping related information like review stars.

ChatGPT Search uses images and structured metadata related to prices and product description, presumably Schema structured data although it’s not explicitly stated. ChatGPT may generate product titles, descriptions, and reviews based on the data received from third-party websites and sometimes may generate summarized reviews.

Merchants are ranked according to how the merchant data is received from third-party data providers, which at this point includes Bing and Shopify.

Ecommerce stores that aren’t on Shopify can apply to have their products included in OpenAI’s shopping results. Stores that want to opt in must not be opted out of OpenAI’s web crawler, OAI-SearchBot .

Featured Image by Shutterstock/kung_tom

Is Your SEO Strategy Built for the AI Era? [Webinar] via @sejournal, @hethr_campbell

The old rules no longer apply. It’s time for a smarter, AI-ready playbook.

AI-driven search is changing the landscape fast. Organic traffic is dropping, visibility is shrinking, and traditional SEO tactics are losing their edge. If you’re still following yesterday’s strategy, you’re already behind.

Join Siteimprove on July 23, 2025 for an exclusive webinar with Zoe Hawkins and Jeff Coyle. Learn how to evolve your SEO approach and content planning to thrive in a world where AI now plays a central role in search.

Here’s what you’ll walk away with:

  • A breakdown of how AI is changing enterprise SEO.
  • Why trust and authority now matter more than keyword volume.
  • How to adapt to high-intent, low-volume traffic behavior.
  • Practical ways to optimize your content for AI search without losing authenticity.
  • The latest tools and frameworks for predictive content planning.

Why this session is a must:

We can no longer rely on the same tactics that worked before. This session gives you an inside look at how SEO must evolve to stay effective in the AI-first future.

Register now to stay ahead of the curve. Can’t attend live? Sign up anyway and get the full replay delivered to your inbox.

TikTok Denies Report Claiming It’s Building a Standalone US App via @sejournal, @MattGSouthern

TikTok has denied a Reuters report claiming it’s building a standalone U.S. app with a separate algorithm.

  • TikTok strongly denies it is developing a separate U.S.-only version of the app.
  • Reuters cites anonymous sources claiming such a project exists, under the codename “M2.”
  • The report highlights the uncertainty around TikTok’s future in the U.S.
Redesigned Shopify onboarding: thoughtful UX, real impact 

Today we’ve launched a redesigned onboarding experience for Yoast SEO for Shopify, built to guide, support, and empower every user from the moment they install. Customer-centric marketers and designers know, first impressions matter, and thoughtful onboarding is the first step to long-term success. 

A new onboarding, designed with care 

We’ve simplified the setup process, removed unnecessary steps, and introduced a guided, narrative-style welcome experience that makes it easier to get started and harder to get stuck. 

Whether you’re new to SEO or scaling a large store, our goal is the same: help you feel confident from the first click. 

“We wanted users to land in the onboarding flow and immediately understand two things: how the app can help them improve their Shopify store’s SEO, and what steps to take first to see results.” Tom Ottjes, UX Designer at Yoast 

Behind the scenes: Service design in action 

This onboarding redesign isn’t just a UI refresh, it’s the result of a service design approach that included: 

  • Journey mapping based on real user behavior 
  • Cross-functional collaboration across UX, development, support and marketing using service blueprints
  • Strategic improvements to both front-end and back-end processes 

Want to learn how a single blueprint helped align our teams and reshape the onboarding experience? 

Read the full story behind the update: Redesigning onboarding for impact 

What’s next? 

We’re already working on the next phase of improvements designed to improve our customers’ experience, including smarter in-app guidance and contextual feature onboarding.   

Thanks to everyone who shared feedback along the way. Keep it coming, we’re listening, learning, and building better together.  

Redesigning onboarding for impact: A service design approach 

First impressions stick, especially in UX. When we saw that new users of our Yoast SEO for Shopify app were skipping key steps or dropping off early, we knew our onboarding wasn’t working. Using journey mapping and service blueprints, we redesigned the experience to be faster, clearer, and more supportive from the start. Here’s how small, well-timed changes made a big difference. 

Table of contents

Launching an improved onboarding experience 

We recently launched a redesigned onboarding experience to help Shopify merchants set up for success. Behind that update is a bigger story: how thoughtful UX decisions, team-wide alignment, and service design methods reshaped the user experience. And we mean that in the broadest sense, from discovery to giving users the feeling that the app is working for them and helping them succeed. 

In this interview, we spoke with our UX designer, Tom Ottjes, who led the project to unpack that process. His answers will offer a closer look at the problems we needed to solve, the tools he used to communicate across teams, and the omnichannel changes that made the biggest difference. 

Before you start reading, here’s a quick animation showing the various parts of the service blueprint we worked on. Of course, there’s much more, but we cannot show you everything.

From patterns to priorities 

Before redesigning a single screen, the team needed a way to understand and communicate what wasn’t working. They needed to uncover what had to change to fix the experience for people in a way that also helped us achieve our company goals. That’s where service design tools, particularly customer journey maps and service blueprints, came in. 

Customer journey mapping helped visualize what users were experiencing from discovery through installation and first use. It highlights not only the steps customers take but also where they become confused, hesitant, or drop off. Based on support conversations, surveys, and analytics, the journey map revealed several issues. One of those issues was a lack of early guidance, which led to missed configuration steps, among other things. 

Before we moved on to action, we wanted to define success by determining KPIs. This is an essential step. It will help shape the direction of the service and experience you will be designing. Instead of viewing onboarding as just a UI problem, the service blueprint mapped every user action alongside the systems, processes, and people behind them. This included content, customer support, notifications, and working within Shopify’s own platform constraints. 

Because it connects what’s visible to the user with what happens behind the scenes, a service blueprint became central to the project. It gave every team, from UX to development, support, and marketing, a shared reference point. By mapping each phase as its own blueprint, the team could prioritize quick wins while keeping an eye on a longer-term onboarding vision. 

It turned a complex, cross-functional issue into something everyone could contribute to. The blueprint helped make improvements easier to design, build, and test in smaller, clearer parts. 

A real example: Turning uncertainty into reassurance for larger stores 

One of the more surprising and important insights from our service blueprinting process was about scale. We discovered that while the app felt fast and responsive for smaller Shopify stores, larger ones had a very different experience. For shops with tens of thousands of products and pages, the initial processing and indexing step could take anywhere from several minutes to a few hours. 

The problem? We weren’t telling users that. Small stores would see their data reflected almost instantly. Large stores would land on a blank dashboard, with no indication that the system was still working in the background. From the user’s perspective, it looked like nothing was happening. 

We addressed this with a series of small but intentional changes. First, we introduced a proper loading state with messaging acknowledging what was happening. Then, we added an email field to that screen, giving users the option to be notified when setup was complete. When they enter their email, they receive a confirmation message once everything is ready. 

It’s a small detail, but one that shifts how the experience feels. Instead of confusion or doubt, users now get feedback, a sense of transparency, and a way to re-engage later. And for us, it’s a concrete example of why aligning the front-end and back-end through service design actually matters. 

Meet the designer

Meet the UX designer: Tom Ottjes

This interview is with Tom Ottjes, one of Yoast’s UX designers. He led the onboarding redesign for our Shopify app and was co-responsible for designing the Yoast AI features. With several years of experience working across product and marketing, his approach centers on translating user behavior into actionable design. Much of his work focuses on simplifying complex flows, improving user guidance, and helping teams understand the customer journey. 

Tom, what problem were you seeing that made this project a priority? 

With our Yoast SEO for Shopify app, we strive to deliver real, tangible value to our users. That starts with understanding their experience from the moment they install the app. Through a combination of user surveys, interviews, support request analysis, and product analytics, we began to see clear patterns emerge. 

There were three main friction points we kept hearing and seeing: 

  1. A lack of guidance: Many users simply didn’t know how to use the app effectively. They installed it but weren’t sure what to do next to optimize their store. 
  2. Unclear value delivery: We noticed that crucial steps, like completing the ‘Site representation’ settings, which unlock immediate SEO benefits, were often skipped. That told us users weren’t seeing the connection between setup actions and real results.  
  3. Hesitation to engage with the free trial: Users were wary of testing the app, unsure of what the trial included or whether it was truly risk-free. 

All of these insights pointed to one thing: the onboarding experience wasn’t doing its job. It wasn’t guiding, reassuring, or demonstrating value early enough. We visualized all these issues in a detailed customer journey map, helping us to zoom out and see broader patterns. We found different user types, where they dropped off, and what confused them. That map became a key alignment tool and helped us frame the onboarding redesign as a top-priority project. 

What would success look like for you from the user’s perspective? 

From the user’s point of view, success meant feeling confident and supported from the very first interaction with our app. We wanted users to land in the onboarding flow and immediately understand two things: how the app can help them improve their Shopify store’s SEO, and what steps to take first to see results. 

That meant offering a smoother, more intuitive experience. An experience that clearly communicated value upfront, provided improved guidance around initial setup steps, and highlighted key features. It should also assure users that trying the app was safe and worthwhile. 

First, we wanted to help users quickly understand the full value of the app. In addition, we wanted users to complete key onboarding actions such as filling out their ‘Site representation’ settings and exploring core features relevant to their store. Emotionally, we aimed for a sense of clarity, trust, and motivation to continue. 

Ultimately, if a user could say, ‘I know exactly what this app does, what I need to do, and I can already see it working for me,’ then we knew we were on the right track. 

The new onboarding helps introduce the app and guides the user through the set up

Can you explain your service design process and how it helped the teams? 

After mapping the current onboarding journey and identifying the key pain points, we knew we didn’t just need a better UI. We needed a more holistic service experience. That’s where service blueprinting came in. 

We started by defining clear KPIs to measure the impact of our changes, such as completion rates for critical onboarding steps, time to value, and feature discovery. These metrics gave us a shared definition of success and helped shape the direction of the user experience. 

Then we used the service blueprinting method to reimagine onboarding as a complete service. A service blueprint maps the relationships between people, processes, and touchpoints tied to a customer journey. It helped us visualize both what the user sees and everything happening behind the scenes to support that experience, from content strategy to customer support workflows to engineering requirements. 

This systems-level view was essential in aligning multiple teams, like UX, development, marketing, and support. Everyone could see how their work connected to the user’s experience and where coordination was needed. It also helped us identify internal gaps, inefficiencies, or dependencies early, so we could design around them. 

To move quickly and deliver value incrementally, we broke the optimized onboarding journey into phases, prioritizing what would have the most immediate impact for users. That approach lets us ship improvements faster while staying grounded in a long-term vision for the onboarding experience. 

We approached the whole effort using a service design mindset. We zoomed out to understand the system users interact with, not just the screens they see. Service blueprinting helped us take what users were experiencing (empathy and insight), identify internal blockers, and structure releases around clear hypotheses. It wasn’t just about delivering onboarding, but about improving the service behind it. 

How are you tracking whether it’s helping users get started faster? 

From the start, we knew that redesigning onboarding wasn’t just about launching something new. We wanted to prove it made a difference. So, we defined clear KPIs to measure the impact of our changes. To make this measurable, we built the tracking infrastructure needed to monitor user behavior at each step. 

But we didn’t stop at numbers. We also incorporated qualitative customer listening tools, things like in-app feedback, support conversations, and interviews. As we wanted to understand how users feel as they move through onboarding. 

Are there still improvements to make? 

Absolutely, because onboarding is never truly ‘finished.’ It’s an evolving experience, and we see it as a continuous opportunity to better support our users. 

The next phase of our optimized onboarding journey will focus on deepening the guidance we provide, helping users go beyond setup and start making more meaningful improvements to their store. We’re looking at how we can better surface insights, suggest next steps based on context, and empower users to unlock even more value with confidence. 

While I can’t share all the details just yet, I can say this: we’re not stopping at getting users through the door. We’re focused on helping them thrive once they’re inside. 

Good things are coming. As always, we’re listening closely to our users to make sure what we build truly meets their needs. 

Pro tips for getting started with service blueprinting 

Thinking of using service blueprinting in your own work? Here are a few things that helped us: 

  • Start with a real journey: Mapping is most useful when it’s grounded in actual user behavior. Use support data, interviews, and analytics to anchor the blueprint in real problems. 
  • Define what “success” means upfront: Before mapping, align your team on what outcomes you’re working toward (e.g., faster time to value, fewer drop-offs). 
  • Map front-end + back-end: Don’t just track what users see. Include internal systems, support workflows, engineering dependencies, and anything that influences the experience. 
  • Keep roles visible: Show which team is responsible for which process. It keeps conversations focused and collaboration smoother. 
  • Don’t overcomplicate: A blueprint doesn’t need to be a polished artifact. Start simple. The value is in getting teams aligned, not in how it looks. 

Blueprinting doesn’t replace good UX research or design, but it’s a powerful way to connect them to the broader experience. If you’re working on anything cross-functional, it’s absolutely worth trying. 

A shared understanding drives real change 

This project wasn’t just about shipping a new flow. We wanted to design with a clear, shared understanding of our users and the processes that support them. 

Our service blueprint turned out to be a great tool to align teams around a single goal: helping users quickly see the value of the Yoast SEO for Shopify app. Along the way, we uncovered friction, mapped dependencies, and built toward something more consistent, supportive, and effective. 

Thoughtful onboarding is the start of everything that follows. By making those early minutes feel clear, calm, and grounded in real outcomes, we’ve not only improved setup times and reached our KPIs but also changed how we work, design, and listen together. 

The work continues, focusing on feature onboarding, improved guidance, and even future WordPress experiences. Together, we’ll apply these lessons from now on. We’ll design by putting users first, build teamwork on transparency, and create experiences that guide, not just onboard. 

Kevin Indig: SEO Has Changed Forever. What Marketers Need To Know Now

If you’ve been affected by AI Overviews, traffic drops, or feel uncertain about SEO’s future, then this episode is for you.

Search Engine Journal’s Editor-in-Chief Katie Morton sits down with growth advisor and author of “Growth Memo,” Kevin Indig, to unpack the results of his latest AI Overviews study.

In this 35-minute episode, they discuss how it impacts search, SEO, and brand marketing in 2025.

Editor’s note: The following transcript has been edited lightly for clarity, brevity, and adherence to our editorial guidelines.

What AI Overviews Mean For Search, SEO & Brand Trust

Katie Morton: Hi, everybody. It is I, Katie Morton. I’m the editor-in-chief of Search Engine Journal, and today I’m sitting down with Kevin Indig, who is a growth advisor to fast-growing tech companies and the author of “Growth Memo,” a fantastic newsletter.

We syndicate it here on Search Engine Journal, but sign up for it directly, too, because he has content exclusive to subscribers. It’s filled with smart insights every marketer needs to know.

Kevin, thanks for making the time today. The study was analyzed in March-April 2025 and published in May. We’ve had time to reflect, and today we’ll unpack the key takeaways.

We’ll start with the nuts and bolts of the study’s background, so listeners understand the context, and then go beyond the data to explore how marketers and companies, especially those frustrated by Google, AI Overviews, or traffic drops, can respond.

So, Kevin, can you summarize the study and share the main takeaways?

Kevin Indig: Thanks for having me on, Katie. It’s great to be here with you.

What The AI Overview Study Really Reveals

Kevin: The study came from a desire to deeply understand, from a qualitative perspective, how everyday users interact with AI Overviews.

In 2024, everyone was eyeing AI Overviews with curiosity, but traffic impact wasn’t significant yet. Then, at the start of 2025, everything changed. It became a “holy cow” moment – this was real and serious.

We asked 70 participants in the U.S., across different age groups, to solve eight tasks that covered dominant user intents: Finding a tax accountant, researching medical questions, shopping, etc.

We intentionally included queries that showed AI Overviews but didn’t tell participants to interact with them – we wanted unbiased behavior.

So, in a nutshell, the three most poignant results are:

1. Classic Organic Results Still Carry Weight

First of all – and this is no surprise – clicks are really rare when people see AI Overviews. That’s gotten through to everyone by now.

And yet, at the same time, classic organic results still have the majority of impact on people’s completion of user journeys.

Let me untangle that for a second: What we found is that people get their final answer – the final piece of information they were set out to get – 80% of the time from classic organic results. Not from AI Overviews, so that was encouraging.

2. High-Quality Clicks Happen In High-Trust Moments

Clicks are going down, but people still click. And each of those clicks has much, much higher quality than, say, in 2024 or before.

Because those clicks are to verify whether the results are accurate, to get human input from platforms like Reddit or YouTube, and to increase confidence in whether what the AI is saying is true.

And for us, that means it’s critical to be present in these high-trust, high-risk moments. I can unpack that a little more…

3. Audience Age Shapes AI Engagement

The third result I found very interesting is that there really is an age difference here. [Younger users] are much more receptive to AI answers. They’re much more active on Reddit and YouTube. Whereas people of a higher age will often just skip the AI answers because they don’t trust them.

You want to know who you’re talking to, who your target audience is. Ideally, what the age group is of your ICP or your target audience, and then make SEO decisions accordingly.

Why Branding Matters More Than Ever

Katie: Thank you for that. What I’d love to talk about next is branding.

I feel like big brands are a little safer with recent developments. If you already have recognition, you’re in a better spot. But if you’re a tiny brand with no recognition, you’re really behind the eight ball.

For the uninitiated or the uninformed, [you might wonder], why is that important? It’s about trust.

When someone sees your brand in an AI Overview, recognition boosts trust. If they click on an AI Overview or scroll to find organic results, they’re more likely to trust and click a name they know. A strong brand increases your chances.

But even strong brands can lose recognition. Mordy Oberstein and I talk about this a lot – he’s doing branding work now. Reputation is everything.

Mordy uses the example of Nike, which was once ubiquitous, but has lost some relevance. Younger generations aren’t as loyal or aware of the swoosh anymore.

So, for big brands, maintaining confidence and trust is critical. For small or new brands, or brands that never had strong recognition, can they still gain traction?

Kevin: You can get traction … but it’s really challenging.

One challenge is that multiple teams need to work together: product, innovation, marketing, support, supply chain. SEO doesn’t control all these variables. It’s always been a discipline of recommendations, relying on others to act.

So, you always were relying on other teams, and that has 10x’d now with AI. Because, as you said, brand, brand perception, and sentiment are so critical to how you appear in search results or answers.

And it goes back to so many different touch points with a brand, not just the logo that people see or the advertising, but also the product that they use, retention, all that kind of stuff.

SEOs need to show other departments where issues lie, using click-through rates, brand search volume, and engagement metrics as signals. They must communicate the story and rally other teams.

But that often runs into cost concerns. Asking for a new call center to improve support has big budget implications, and quantifying ROI is tough.

So, SEOs must push beyond the Google channel and influence company strategy. It’s incredibly difficult to influence.

Katie: Absolutely. And speaking of SEO being declared “dead,” I’ve heard that every few years in my 20 years in the industry, but this is the first time I’ve felt a credible threat.

SEO will never truly die. It’s discovery, and discovery is always needed, but it’s definitely changing. It used to be the most cost-effective marketing channel. Now, ROI is less certain, and budgets are contracting.

But there’s a silver lining. A lot of low-quality, general content meant just to drive mass page views is getting weeded out.

For example, we used to rank for “What is E-E-A-T?” and get tons of unqualified traffic. With AI Overviews answering those general queries now, traffic is down, but the remaining traffic is far more qualified. That’s better for conversions.

It’s hard for publishers who relied on brute-force clicks. But for us, shifting away from programmatic and toward advertisers aligned with our audience, like SaaS, has worked. The industry is changing massively.

So, what do you think is next for SEO and marketing?

The New Role Of SEO In A Changing Landscape

Kevin: You hit it on the head. SEO is contracting; budgets are down, leadership confidence is down, and when people leave, their roles often aren’t replaced. SEO has died and reinvented itself many times.

I see that we’re using a lot of SEO also for AI visibility optimization. I do expect that to change, but however you flip it, we are in a transition period. And the problem with transition periods is that they’re hard to navigate. You lose orientation, and it’s painful.

Once you settle at a new baseline, you just run around a little headless, and you try to find your way. And then slowly, things kind of start to settle back in.

And so I’m very confident that whatever we’re going to call this, we’re going to settle into a new baseline. It might take a while. This is not going to stop in the next six months – probably not twelve months. But it’s hard to predict when.

Based on how quickly models improve and how quickly humans adapt to them, that will decide the pace of this transition.

However, there are also many opportunities in transitions. You can reinvent yourself. And that’s where, as SEOs, we might lose the SEO budget, but maybe we gain some brand budget, which has been much, much bigger in the past.

You see companies spending millions of dollars for multi-year contracts for a tiny logo that sits somewhere on a Formula 1 car. These things happen all the time.

There’s a big opportunity for SEO to detach from that unwanted profiling as a performance channel – detach ourselves from being a performance channel, and become much more of a brand channel, influence channel, presence channel – whatever you want to call it.

New metrics. New levers. Deeply rooted in SEO. And effective and powerful, but kind of in a new design, right? Like SEO 2.0. Whatever you want to call it.

And I do agree with you. I also see people who’ve been in the game for a long time stepping out. Totally get that. I see young people losing a bit of confidence.

But I will also say that I would like (but wouldn’t admit) that there’s a little part of me that’s kind of excited for all this change.

Because it’s an opportunity to kind of reshuffle the cards, find out new stuff, maybe find some secrets, and kind of reverse engineer what’s going on.

When you look at the last just 10 days where multiple people and companies found new ways to reverse engineer what queries Gemini uses and ChatGPT uses, I’m like, man, it’s awesome to see how adamant the industry works on developing the new playbook, dissecting how these mechanics work and LLMs work, and finding new ways.

So, I have high confidence, and I also have a lot of empathy for all the pain and the kind of problems that this industry is going through. But again, I see us coming out the other side at some point in like a new design – and with a lot of impact.

Katie Morton: I love it. I agree with the empathy as well. Because everyone in marketing, it seems, has lost their mind a little bit over the past year or two with these shifts in traffic.

But that Wild Wild West environment is also really exciting because there are going to be all of these developments.

And if people are calm and they persevere and they do the work to figure these things out, either for themselves or to watch what those researchers are finding, people will be okay, right?

Kevin: We always are. Sorry to cut you off there, but there’s a really important point to make here that I didn’t make – and that is: It’s not just search that’s changing.

SEO is at the forefront of AI. At the absolute forefront. Because it’s about words, and it’s about search, and search is kind of the biggest interface between AI and humans right now.

So it’s not just search that’s changing. Marketing is completely changing. And like, all of our lives are completely changing.

Sure, this will take years to trickle through, maybe not even to the degree we’ve thought of it, but it’s pretty clear that AI is at least as revolutionary as the internet. Maybe even the most revolutionary invention that humanity has made so far.

So let’s not forget: Everything is changing. It’s not just us SEOs. It’s all the channels. It’s marketing as a whole.

Modes and levers are disappearing, and new ones are coming up. We’re feeling it deeply in SEO, as being kind of the front line of AI. But make no mistake, this will trickle through to all the paid channels, product, everything.

Everybody is in a state of shock right now, trying to figure out what the new branches are to hold on to and then build on top of. Marketing as we know it is over. LLMs are transforming how they reach us.

Katie: This affects every channel. At SEJ, we’ve collapsed editorial and marketing into one integrated team. It used to be SEO and editorial here, marketing over there, and no one really talked. That doesn’t work anymore.

Now, everything is more cohesive and focused on the ICP and conversion. It’s better for customers and for teams.

Kevin: 100%. I talk to all my clients about this. SEO and paid search should’ve always been connected, but they were siloed, same with product, email, social, etc.

I mean, look: Realistically and ideally, SEO and paid (or paid search) have always been connected at the hip. But I’ll tell you, at least across almost all the companies that I’ve worked with, they were siloed.

The same exists with all these other teams, like product marketing or social media, conversion, and email – all that kind of stuff.

Now’s the time to rip off the band-aid. There can be small teams of maybe an SEO, an editor, an email person, a social person, and maybe a very technical person who can quickly prototype new apps, programs, or tools.

The biggest challenge now is internal red tape. AI is a speed catalyst, but companies’ old workflows slow them down. Big organizations are stuck.

I’m urging clients to form these multi-disciplinary units under one manager, one roof, one mission.

Reaching People Everywhere Requires A Bold Shift To Other Platforms

Katie: Awesome. One last point: other platforms. For too long, people relied too heavily on Google. Diversifying traffic sources – ads, social, newsletters – is now essential. Holistic marketing is the future. What are you seeing [that is] working right now?

Generally speaking, where do people live these days? Where are humans hanging out, and where do we find them? What are the success metrics that you’re seeing?

Kevin: The short answer is: Everywhere.

Katie: Good luck, everyone. Okay, good night. That’s the show!

Kevin: No, but the reality is, everywhere. There’s this interesting paradox. I need to coin this term somehow, but this interesting paradox that basically all the social networks are growing. And new ones are popping up, right? TikTok – I mean, it’s not that new anymore, but it’s still growing. Reddit is becoming much more of a household name now.

And so you ask yourself, what gives? Sure, linear TV’s down, okay. But how is this possible? And the reality is: People are online all the time – speaking for a friend – and they use a lot of platforms at the same time.

So, the best teams, or the companies that are making a big impact, they have this surround sound effect that they’re creating, where they’re present in a lot of places. They engage authentically, say, on Reddit.

When good companies engage on Reddit, it doesn’t feel like marketing. It’s not marketing, really. It’s much more like trying to be helpful, more like customer support or success.

That’s why these people are generally very well-suited to interact on Reddit. They truly add value. They’re truly part of the conversation.

Brands are repurposing their content in a very thoughtful and high-fidelity way, where maybe they create a blog article, turn it into a video, turn it into clips, which then turn into questions they answer on Reddit. There is this kind of everywhere strategy. AI really helps with that.

And I will also say it’s typically not companies that are getting stuck at the quantification-of-impact question. The reality is that steering an organization or a company toward that multi-channel effect – or that surround sound effect – takes a swing.

It takes a leader to say, “Okay, we’re going to spend some money and take six months, and we’re going to invest in Reddit and YouTube, and we’re going to wait for the results to come in. We’re not going to sit there every day refreshing the dashboard asking, ‘How many sales have we generated yet?’”

It takes a bit of a swing. And so it’s defining for this era, for this transition period, where it’s much harder to project and forecast where you’re going to land with some of these things.

It takes judgment and taste and a certain degree of risk-taking to invest in these channels and functions, and being comfortable, or at least okay, with waiting for some of the results to come in and being able to measure them later.

I’m not saying you should wait a year or two. But give it two quarters, maybe three quarters, and experiment with some of these channels.

So, that’s where people are – people are everywhere. It’s not enough to just have one shot at one platform. You need to be kind of everywhere.

And repurposing can help. Using AI with some of these things helps. But at the end of the day, you need to take a swing.

Katie: Very wise, Kevin. One of those things that I found highly annoying is that you can run these experiments, and you’re going to wait for your results, and then before your experiment is even done, everything’s changed again.

Kevin: Exactly. Predictable methods are gone. You take swings, and some won’t connect because conditions change. The best leaders, the best teams – a lot of times, they take a lot of swings.

Because some of those swings will hit full force, and it’s kind of a skill to build.

Katie: Yeah, I couldn’t agree more. We’ve implemented monthly experiments at SEJ. Every department runs one. It could be layout, content type … constant iteration. I tell the team: soft knees. Be ready to shift. There’s no “set it and forget it” anymore.

Kevin: Yes, yes. On point. Allow people to fail. Another good skill is being able to take meaningful risks. I’m not saying bet the farm, but as a leader, if you want to encourage your people to take risks, let them.

Again, that doesn’t mean to blindly shoot in all directions. You want to have some thought behind that, some judgment. You want to be critical. But there has to be a point at which you let go.

Katie: That is a really perfect point. We tie experiments to north-star metrics. For us, one is newsletter subscriptions, so most of our experiments support that. We’ve seen great success, not always in raw traffic, but in conversions and revenue.

Kevin: Amazing. Congratulations on that.

Katie: Thank you. All right, Kevin, any parting remarks before we head out?

Kevin: I’m hearing a lot of very concerned SEOs. Concerned about “How do I tell this story?” or “How do I manage my boss or leadership in this time where traffic is down?”

I want to send out some courage. This is one of the biggest shifts I’ve lived through in my life. I would bet it’s probably the same for most, if not all, of the audience.

So, this is maybe the time to make some changes and have some grace about finding a new playbook.

I’m seeing a lot of SEOs very scared about this. I get the initial fear. But again, this is such a substantial, fundamental change. It’s okay for things to look different. It’s okay for you not to have the answer right now. Be honest with leadership. Push back if needed.

Katie: Focus on new metrics, not just UVs or PVs, but ones that connect to business goals. That’s where the story of success will be told.

Kevin: Exactly.

Katie: Thanks again, Kevin. Where can people find you?

Kevin: growthmemo.com, or just search for “Growth Memo.” That’s my main hub.

Katie: Awesome. We’re at searchenginejournal.com. See you next time!

Kevin: Thanks for having me.

More Resources:


Featured Image: Paulo Bobita/Search Engine Journal

Ask An SEO: Should I Hire Candidates Who Can Use AI Tools Or Have Traditional Skills? via @sejournal, @HelenPollitt1

In this week’s Ask An SEO, a marketing manager asks which SEO skills are most valuable to look for in candidates today, especially with AI in the mix:

“I’m a marketing manager who’s been tasked with hiring our first in-house SEO specialist.

With AI tools becoming more prevalent, what skills should I prioritize when interviewing candidates in 2025? Are traditional SEO skills still as valuable, or should I focus more on candidates who can work alongside AI tools?”

This is a great question, and one I imagine a lot of hiring managers in the marketing industry are asking themselves.

For years, we’ve been looking for SEO professionals with skills that will help our websites thrive in Google, Bing, and Yandex. But, what skill set is needed for the emerging markets of ChatGPT, Perplexity AI, and Claude?

And what about keyword research, content creation, and technical audits? Are they still useful activities for SEO professionals to carry out manually when there are so many AI tools purporting to be able to do this for you now?

What Traditional SEO Skills Are Still Needed

We often think of skills within traditional SEO fitting roughly into three categories: technical, content, and authority-building. Are these still needed in the era of large language model (LLM) platforms and tools?

Technical SEO Skills

Ensuring that a website can be crawled, rendered, parsed, and indexed effectively by bots has been a staple of SEO for a long time.

If the bots can’t access the pages you want to have ranked, can’t read the content on them, or find the page to be unfriendly for users, you will struggle in the traditional search engine results pages (SERPs).

This isn’t all that different in the new world of generative engine optimization (GEO). Bots still need to be able to access content on your website, read it, and understand it.

Technical SEO skills will continue to be important to online visibility in the new era of organic discovery.

An excellent SEO will be someone who can utilize AI tooling to automate and speed up the checks they are already performing. The really valuable technical SEO skills will still be analyzing, prioritizing, and communicating the issues when they are discovered.

Good technical SEOs have been looking at ways to automate their processes using Python and Structured Query Language (SQL) for a while now.

AI is enabling them to do this quicker, and for those who are newer to those languages, to automate their processes more easily.

Hire SEO specialists who are excited to use AI tools to enhance their work, not replace it entirely.

You will still need SEO pros to be creative in problem-solving and working within the confines of your organization’s technology, resources, and capabilities.

Read more: 15+ Technical SEO Interview Questions For Your Next Hires 

Content Skills

AI-written content has been a hot topic for a couple of years now. Can AI replace human writers? Should you hire with content creation and marketing skills in mind, or can you leave that purely to AI now?

I would suggest that any SEO hire you make needs to understand how to craft engaging copy that clearly defines the brand and meets the needs of users at each stage of the buying journey.

This hasn’t changed much from when SEO pros brief writers and graphic designers in content creation. We still need SEO specialists to understand how to request engaging content, whether that be through AI or human creators.

The ability to define what will be engaging content through research (whether keywords or prompts) and how users engage with it (whether on the brand site or within the LLM’s answer) is still critical.

Read more: Generative AI And Social Media: Redefining Content Creation

Authority-Building Skills

Previously, there was an evolution in SEO from regarding authority building as getting backlinks by whatever means necessary, to acquiring links through engaging and relevant content.

For optimization in LLMs, the desire is more to cement a brand’s positioning and sentiment through mentions on other authoritative websites.

The skill set needed to acquire authoritative links through digital PR will not be that different from what’s needed to acquire mentions.

In fact, good digital PRs have recognized for a while now that brand mentions are valuable in their own right.

There is a need to understand the publisher who is being targeted, what they write about, when best to contact them, and how. This could well be automated to a good degree by AI.

However, the really excellent PRs build up relationships with their contacts, so they are front-of-mind when a story is breaking. This is something AI will struggle to replace.

When hiring for the digital PR side of SEO, look at their relationship-building skills in particular.

Read more: 3 Types Of PR & SEO Funnels That Will Maximize Conversions

Analytical Skills

AI has (thankfully!) taken much of the pressure off SEO professionals to be efficient mathematicians, proficient in Excel formulae, or, at least, having a good percentage calculator tool bookmarked.

Summarizing increases and decreases in key performance indicators (KPIs) is something AI can handle. It can highlight correlations between metrics and identify likely causes. AI can also summarize this all into a compelling report.

But, it still needs a human to determine if its recommendations are valid and a viable course of action.

A good SEO will be someone who can utilize the AI tools to draw conclusions and highlight issues, while retaining strategic oversight.

Strategy

That leads on to strategic skills. Good SEO pros will be able to utilize AI tooling for processes while drawing on their own deep contextual understanding and common-sense reasoning.

Hire SEO professionals who are adept at considering the moral and ethical implications of marketing and who can adapt to novel situations.

AI tooling will not be able to build trust with senior stakeholders. It will not be able to inspire and influence them. It definitely will not be able to manage egos and emotions like a good SEO has to.

Skills That Help In Emerging Markets

Beyond the skills that we’ve long been looking to hire for in SEO, it’s important to find people who are able to thrive in a burgeoning environment.

Great SEO pros have been cultivating these skills throughout their careers. Bad SEO professionals have scraped by on second-hand knowledge and following templated procedures.

Experimental Approach

Make sure they have the ability to experiment and apply their learnings.

We’re entering a new phase of SEO where what worked before might not work again. There are no experts in GEO yet; we’re all having to learn as we go along.

Make sure your candidates are willing to learn from trial and error.

Understanding Of How To Work With Uncertainty

The days of following an audit template are both long-gone and a way off. We can’t just apply what we know from SEO directly to GEO.

We need to learn what works in those new platforms. That means good SEO pros are going to have to be comfortable with the uncertainty in their industry again.

Seasoned SEO professionals will remember back to this during their formative years in the industry, but newer SEO specialists will need to break free of the “this is what works for SEO” mentality and be OK with adapting on the fly more.

Ability To Problem Solve And Investigate

This means they will really need to be keen problem-solvers. SEO, at its root, has always been about problem-solving.

With the suite of AI tooling growing, the temptation to delegate critical thinking to a machine will be great.

However, SEO pros will still need to be able to take a step back, consider all the context and angles, and work toward a solution given the resources and constraints they face.

This means that they cannot rely solely on AI to help them.

Read more: LinkedIn Lists Top 15 In-Demand Skills, Makes Related Courses Free

Hire For Complementary Skills

The answer to your question is yes. To both.

You need someone who can work alongside AI tools as well as having traditional SEO skills.

The experience and qualities of a seasoned SEO professional will still be extremely useful in the emerging world of LLMs and AI tooling.

It would be a risk to your organic performance if you hire solely based on whether the candidate can utilize AI tools well.

However, you do want to make sure the SEO pro is using all of the advantages that AI can bring. They need to be able to adapt to new technology and processes.

How To Interview For SEO Skills That Complement AI Solutions

The curiosity about new technology. The desire to experiment and adapt. Having an open mind to change. These are all attributes of good SEO professionals that are more important now than ever before.

When considering whether an SEO professional is a likely good fit for your role, find out their approach to new situations.

See how they have adapted in the past to changes in SEO that needed a change of tactics.

Ask them how they have diagnosed and responded to algorithm updates, or expanded their skill sets to include social media search engines.

Summary

In essence, the need for traditional SEO skills is not diminishing. However, great SEO professionals will be those who can adapt their skill set to work in GEO, as well as make the best use of new AI tooling available to them.

Alongside that, problem-solving, experimentation, and a keen strategic approach are what to look for in your next SEO hire.

More Resources:


Featured Image: Paulo Bobita/Search Engine Journal

OpenAI And Perplexity Set To Battle Google For Browser Dominance via @sejournal, @martinibuster

Credible rumors are circulating that OpenAI is developing a browser. However, the timing of the anonymous tip is curious, because Perplexity coincidentally announced they are releasing a browser named Comet.

It’s a longstanding tradition in Silicon Valley for competitors to try to overshadow competitor announcements with competing announcements of their own, and the timing of OpenAI’s anonymous rumor seems more than coincidental. For example, OpenAI leaked rumors of their own competing search engine on the exact same date that Google officially announced Gemini 1.5, on February 15, 2024. It’s a thing.

According to Reuters:

“OpenAI is close to releasing an AI-powered web browser that will challenge Alphabet’s (GOOGL.O), opens new tab market-dominating Google Chrome, three people familiar with the matter told Reuters.

The browser is slated to launch in the coming weeks, three of the people said, and aims to use artificial intelligence to fundamentally change how consumers browse the web. It will give OpenAI more direct access to a cornerstone of Google’s success: user data.”

Perplexity Comet

According to TechCrunch, Perplexity’s Comet browser comes with its Perplexity AI search engine as the default. The browser includes an AI agent called Comet Assistant that can help with everyday tasks like summarizing emails and navigating the web. Comet will be released first to its $200/month subscribers and to a list of VIPs invited to try it out.

There’s something old-school about Google, Perplexity, and OpenAI battling it out for browser dominance, a technological space that continues to have relevance to users and perhaps the one constant of the Internet, which is that and pop-ups.

Google’s Quality Rankings May Rely On These Content Signals via @sejournal, @martinibuster

The average SEO strategy begins and ends with keyword research, with keyword volume as the deciding factor in what topics will be written about. It’s an outdated approach that fails to resonate with users and no longer reflects how modern search engines evaluate content. Content that delivers a meaningful experience across the factors that matter most to users earns trust, signals quality, and attracts links, shares, and higher rankings.

User Behavior Has Always Been A Part Of Search Ranking

User signals play a central role in Google’s ranking algorithms and the recent antitrust lawsuit against Google revealed how important these are.

One of the exhibits in the recent DOJ antitrust trial against Google featured a confidential presentation called Ranking For Research where Google noted that user behavior signals are noisy and that it takes a lot of data in order to see the patterns.

They wrote (PDF):

“The association between observed user behavior and search result quality is tenuous. We need lots of traffic to draw conclusions, and individual examples are difficult to interpret.”

Another Google document stated that user interaction signals are important to search rankings (PDF):

“…not one system, but a great many within ranking are built on logs. This isn’t just traditional systems, like the one I showed you earlier, but also the most cutting-edge machine learning systems, many of which we’ve announced externally– RankBrain, RankEmbed, and DeepRank.”

Google has used many kinds of user behavior signals for ranking purposes:

  • The Google Navboost patent ranks pages based on user interaction signals.
  • Google’s Trust Rank patent describes an algorithm that relies on user trust signals to identify trustworthy sites and then identifies sites that are linked from those user-trusted websites.
  • Google’s Branded Search patent describes an algorithm that uses navigational queries as implied links for ranking purposes.

PageRank is commonly thought of as just a link algorithm but it’s actually a way to leverage user signals in the form of the links they publish on websites. It’s also a model of user behavior because the linked nature of the web can be used to indicate which sites a user is likely to visit.

Google’s PageRank research paper explains:

“PageRank can be thought of as a model of user behavior.”

Do Keywords Matter Anymore?

Yes, keyword still matter. But it’s been a long time since exact match keywords were a major factor that determined which sites are ranked. Look at virtually any search result and you’ll see that many top ranked sites do not contain an exact match for the keywords in a search query.

Content strategies that rely on keyword-based hubs or silos should be given a second look. Those kinds of strategies originated in the earliest days of search engines when adding exact match keywords into titles and headings was a sure way to be ranked.  That’s no longer the case, so why are SEOs still stuck with keyword-based strategies that map keywords to a hub and spoke content strategy.

Logical site structure is a part of a quality user interface and makes it easy to find content. Focus on that and interlink in ways that make sense to users.

Try thinking in terms of topics that users are interested in and see how far that takes you.

Write With The Purpose To Be Understood

I’m going to share an advanced concept about writing that helps sentences, paragraphs and entire web pages reach an audience more effectively.

Cognitive Load

There is a scientific concept called cognitive load. In the context of reading, cognitive load is the amount of mental effort used to process information.

For example, sentences with confusing instructions or jargon can take extra effort to process. When the load exceeds a certain threshold, the person’s ability to understand or learn from what they’re reading suffers.

Cognitive Dissonance

I have my own theory that’s similar to cognitive load that I call cognitive dissonance. It’s not something scientific that I read, it’s just my own theory.

Dissonance means a lack of harmony, when sounds clash. Poor writing can be dissonant due to the choice of words that are abstract (lack a clear meaning or have multiple meanings) , using jargon, or simply using words that aren’t commonly understood.

Another source of dissonance is writing a paragraph that rambles rather than builds up to an idea.

Cognitive dissonance causes a reader to lose track of what they’re reading and consequently engage less with the content.

Here’s the same sequence of paragraphs you just read, with an explanation of their purpose:

1. Define the idea: I explain that I have a personal theory

I have my own theory that’s similar to cognitive load that I call cognitive dissonance. It’s not something scientific that I read, it’s just my own theory.

2. Explain my idea with a definition and metaphors

Dissonance means a lack of harmony, when sounds clash…

3. Apply the metaphor to writing:

Poor writing can be dissonant due to the choice of words…

4. Expand the definition to paragraph structure

Another source of dissonance is writing a paragraph that rambles rather than builds up to an idea.

5. The big idea I was building up to: What it all means

Cognitive dissonance causes a reader to lose track of what they’re reading and consequently engage less with the content.

SEOs like to talk about hooks and other little tricks to writing, but good writing is not about tricking the user. It’s about clear communication. It doesn’t always come out right the first time the words spill onto the page. Sometimes it helps to step away and come back to it for the errors in sentence and paragraph structure to become visible.

Crafting Content Around the User Experience

Publishers who build sites around keywords face an uphill struggle obtaining links, and since links remain an important ranking factor, it makes sense that the SEO strategy works together with obtaining links. This is where user experience marketing shines.

Nobody links to a keyword-based site because the keywords make them feel good about the site. Keyword-based sites feel sterile because they are optimized for keywords, not people. That approach also results in a made-for-search-engine website structure. Nothing screams “made for search engines” like sitewide title tags with keywords ripped from Google’s People Also Asked keyword lists.

What I would suggest is to acquaint yourself with who you’re writing for by speaking to people who are interested in your topic, joining some Facebook groups, checking out popular forums, listening to podcasts about the topic, watching YouTube videos about your topic, and reading the comment sections of those videos. This will not only give you an idea of what people are talking about, it will show you how they’re talking about it and quite possibly give you ideas for your business, whether that’s selling things online or writing about a topic

Users Share Experiences, Not Links

Perhaps the best kind of link is the kind created because of a positive experience (learning, usefulness, fun). Scientific research has discovered that experiences motivate sharing and that positive experiences are shared the most.

Insight: Those aren’t just links that people are sharing.  Links from one website to another website or even on social media, are the expression of the experiences people had with a website.  Cultivate positive experiences and people will begin linking and sharing your website.

Insight: Devoting time to the user experience is a pragmatic approach to promoting a website because inspiring site visitors with emotional resonance, a feeling, is a sure way to encourage more sales, more links, and more traffic. And that’s why we optimize, right? To make more money.

Make Visitors Want To Return

  • Make your content (even if they’re products) easily viewable from the top of the fold
  • Make your content easy to scan (with headings)
  • Offer related articles at key points where visitors tend to become disinterested
  • Encourage messaging opt-ins

Post-Transaction Experience

Successful entrepreneur Justin Sanger pointed out that everyone knows about the sales funnel, but less well known is the funnel that opens up after the sale. He calls this upside-down funnel the Post-Transaction Funnel. The Post-Transaction Funnel represents all the things you can do to send a signal back to the search engines that site visitors had a good experience at your website. This activity includes:

  • Encouraging social sharing
  • Cultivating good reviews
  • Encouraging word of mouth referrals
  • Cultivating relationships with non-competitors in your space

I believe it is a good practice to consider the post-transaction funnel because those are the kinds of activities that tend to cultivate more sales. Post-transaction marketing is something to consider outside of the Classic SEO box.

Watch Justin Sanger Discuss Post-Transaction Funnel

Takeaways: User Experience Marketing

1. User-behavior signals are used within Google’s various algorithms and machine learning systems as evidence of page quality and trust.

2. Logically considered, visitor-friendly sentence, paragraph, page, and site architecture that makes it easy to understand information supports strong quality signals.

3. Content that uses clear, jargon-free sentences and paragraphs that build logically enables readers to process information effortlessly and helps build a better user experience.

4. Content planned around user experience rather than exact-match keywords makes pages feel more human-centered and less like they were made for search engines, which contributes to greater trust.

5. Positive emotional experiences that motivate natural sharing and backlinks act as strong indicators of authority and trust.

6. Page design that includes above-the-fold visibility, scannable headings, related-article prompts, and opt-ins helps keep visitors engaged, active, and returning, reinforcing external content quality signals.

7. Post-transaction funnel actions, such as encouraging reviews, social sharing, and word-of-mouth referrals, feed satisfaction signals back to search engines and strengthen trustworthiness.

It is important to recognize that the foundation of a successful website is the user experience. Even a successful PPC landing page is crafted with the principle of a quality end-to-end user experience, from the layout and ease of data delivery to convenience.

User experience marketing is about moving beyond simple keyword phrase optimization, with a content strategy built on understanding what that content means to the user. Is it important? Is it entertaining? Does it rock, and does it roll?

Relevance is still king, but the definition of relevance is now focused on the user, not your keywords.

Featured Image by Shutterstock/Andrii Nekrasov

Why the AI moratorium’s defeat may signal a new political era

The “Big, Beautiful Bill” that President Donald Trump signed into law on July 4 was chock full of controversial policies—Medicaid work requirements, increased funding for ICE, and an end to tax credits for clean energy and vehicles, to name just a few. But one highly contested provision was missing. Just days earlier, during a late-night voting session, the Senate had killed the bill’s 10-year moratorium on state-level AI regulation. 

“We really dodged a bullet,” says Scott Wiener, a California state senator and the author of SB 1047, a bill that would have made companies liable for harms caused by large AI models. It was vetoed by Governor Gavin Newsom last year, but Wiener is now working to pass SB 53, which establishes whistleblower protections for employees of AI companies. Had the federal AI regulation moratorium passed, he says, that bill likely would have been dead.

The moratorium could also have killed laws that have already been adopted around the country, including a Colorado law that targets algorithmic discrimination, laws in Utah and California aimed at making AI-generated content more identifiable, and other legislation focused on preserving data privacy and keeping children safe online. Proponents of the moratorium, such OpenAI and Senator Ted Cruz, have said that a “patchwork” of state-level regulations would place an undue burden on technology companies and stymie innovation. Federal regulation, they argue, is a better approach—but there is currently no federal AI regulation in place.

Wiener and other state lawmakers can now get back to work writing and passing AI policy, at least for the time being—with the tailwind of a major moral victory at their backs. The movement to defeat the moratorium was impressively bipartisan: 40 state attorneys general signed a letter to Congress opposing the measure, as did a group of over 250 Republican and Democratic state lawmakers. And while congressional Democrats were united against the moratorium, the final nail in its coffin was hammered in by Senator Marsha Blackburn of Tennessee, a Tea Party conservative and Trump ally who backed out of a compromise with Cruz at the eleventh hour.

The moratorium fight may have signaled a bigger political shift. “In the last few months, we’ve seen a much broader and more diverse coalition form in support of AI regulation generally,” says Amba Kak, co–executive director of the AI Now Institute. After years of relative inaction, politicians are getting concerned about the risks of unregulated artificial intelligence. 

Granted, there’s an argument to be made that the moratorium’s defeat was highly contingent. Blackburn appears to have been motivated almost entirely by concerns about children’s online safety and the rights of country musicians to control their own likenesses; state lawmakers, meanwhile, were affronted by the federal government’s attempt to defang legislation that they had already passed.

And even though powerful technology firms such as Andreessen Horowitz and OpenAI reportedly lobbied in favor of the moratorium, continuing to push for it might not have been worth it to the Trump administration and its allies—at least not at the expense of tax breaks and entitlement cuts. Baobao Zhang, an associate professor of political science at Syracuse University, says that the administration may have been willing to give up on the moratorium in order to push through the rest of the bill by its self-imposed Independence Day deadline.

Andreessen Horowitz did not respond to a request for comment. OpenAI noted that the company was opposed to a state-by-state approach to AI regulation but did not respond to specific questions regarding the moratorium’s defeat. 

It’s almost certainly the case that the moratorium’s breadth, as well as its decade-long duration, helped opponents marshall a diverse coalition to their side. But that breadth isn’t incidental—it’s related to the very nature of AI. Blackburn, who represents country musicians in Nashville, and Wiener, who represents software developers in San Francisco, have a shared interest in AI regulation precisely because such a powerful and general-purpose tool has the potential to affect so many people’s well-being and livelihood. “There are real anxieties that are touching people of all classes,” Kak says. “It’s creating solidarities that maybe didn’t exist before.”

Faced with outspoken advocates, concerned constituents, and the constant buzz of AI discourse, politicians from both sides of the aisle are starting to argue for taking AI extremely seriously. One of the most prominent anti-moratorium voices was Marjorie Taylor Greene, who voted for the version of the bill containing the moratorium before admitting that she hadn’t read it thoroughly and committing to opposing the moratorium moving forward. “We have no idea what AI will be capable of in the next 10 years,” she posted last month.

And two weeks ago, Pete Buttigieg, President Biden’s transportation secretary, published a Substack post entitled “We Are Still Underreacting on AI.” “The terms of what it is like to be a human are about to change in ways that rival the transformations of the Enlightenment or the Industrial Revolution, only much more quickly,” he wrote.

Wiener has noticed a shift among his peers. “More and more policymakers understand that we can’t just ignore this,” he says. But awareness is several steps short of effective legislation, and regulation opponents aren’t giving up the fight. The Trump administration is reportedly working on a slate of executive actions aimed at making more energy available for AI training and deployment, and Cruz says he is planning to introduce his own anti-regulation bill.

Meanwhile, proponents of regulation will need to figure out how to channel the broad opposition to the moratorium into support for specific policies. It won’t be a simple task. “It’s easy for all of us to agree on what we don’t want,” Kak says. “The harder question is: What is it that we do want?”