AI Search and SEO: How the Industry is Navigating a “26-Mile Sprint”

The End of Traditional SEO Checklists

The urgency of transformation was emphasized early in the discussion:

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“If you haven’t gotten your ducks in a row with traditional SEO at this point, a lot of people aren’t going to help you anymore because we’re moving,” declared one expert, expressing frustration with practitioners still struggling with basic implementation after 20 years of industry development.

The sentiment reflects growing impatience with what experts see as oversimplification of increasingly complex challenges:

“Now is not the time to go back and learn what structured data is or how to deploy it. Like if you’re having those conversations, I kind of want to tell you here’s some remedial studying for the weekend. Come back to me when you’re serious about moving forward because you had 20 years to get that done and you’re still struggling.”

The intensity of required adaptation was described in stark terms:

“We are moving so fast now that it is a sprint. It is a 26-mile sprint. There is no more example of oh it’s a marathon. It’s a sprint. No, it’s all a sprint and it’s infinitely long and you either can keep up or you cannot.”

Barry Schwartz, veteran industry observer and founder of Search Engine Roundtable, noted that successful SEOs have always adapted to change:

“SEOs who are around today that were around 20 years ago are always stepping up. They’re always, it used to be back in the old days, submit your page to the index and submit them to 20 different search engines over and over again, every single day. Then it was new on page SEO, then link building, then universal search came out, feature snippet optimization… We’re constantly stepping stuff up.”

However, the current transformation represents a quantum leap in complexity and scope. Schwartz acknowledged the unprecedented nature of current changes:

“Yes, this is a huge jump in terms of what SEOs are adding to their plate. A lot of SEOs were focusing on like one thing or two things. Now you really need to have everything under your belt to make this possible.”

Traffic Hemorrhaging and Revenue Model Disruption

Multiple panelists confirmed significant traffic losses across client portfolios, with some reporting declines of 20-60% as AI systems provide direct answers rather than driving users to websites. Mike King, a prominent SEO consultant, revealed he had been preparing clients for these changes:

“We’ve been educating our clients on how the channel is changing for like the last two years. I wrote a blog post on this very site like two years ago talking about how retrieval augmented generation was going to change everything about our space and how everyone was going to see losses between 20 and 60% in traffic. Here we are.”

King noted how client attitudes shifted once theoretical predictions became measurable business impacts:

“We’ve been telling clients that for a while and they were at first they’re like cool cool whatever. And then once they started seeing these impacts from AI overviews, they’re all ears.”

The transformation is particularly pronounced among younger demographics:

“We see that Gen Z really like these AI systems and how the content is surfaced for them. So if they are going to be the next user base large user base then perhaps we need to figure out how to get value out of these results for publishers as well.”

Industry Rebranding and the Rise of “GEO”

A significant debate emerged around industry terminology, with some experts advocating for “Generative Engine Optimization” (GEO) as a distinct discipline from traditional SEO. Mike King argued that rebranding opportunities have been missed:

“That ship has sailed, guys. Like as soon as Andre Horowitz was like this is generative engine optimization, that’s what it is. As soon as the media starts saying this is generative engine optimization, that’s what it is. We can push back all we want, but it’s too late. We should have done that a year ago when this thing first popped up rather than just saying it’s more SEO.”

The naming debate reflects deeper questions about professional identity and compensation. Despite managing channels worth billions of dollars, SEO professionals often earn significantly less than counterparts in media and advertising:

“You’ve got VPs of SEO at massive organizations making like 300 grand, but they manage a channel that yields billions of dollars and they’re only getting 300K. Like that’s a pretty big disparity, whereas you’ve got people in the media side that are making closer to like 5600.”

King emphasized the broader opportunity for industry repositioning:

“You’ve been the janitor for the web, for Google for the last 20 years. Like, you deserve more.”

New Skills and Cross-Discipline Requirements

The transformation demands fundamentally different skill sets and collaborative approaches. Miriam Ellis, a local SEO expert, emphasized that modern practitioners must work across traditional silos:

“We now have to actually grow up and maybe be polite and learn how to deal with others. You’re no longer like I’m nobility. Yay. I don’t care what you say. I’m number one. We now have to actually grow up and maybe be polite and learn how to deal with others.”

Dwayne Forrester stressed the urgency of skill development with a stark warning:

“If you are hiring someone to do keyword research now and you think somehow miraculously in 2 years they will be an expert at the concept of query fan out and how to utilize that information in a content context. You’re delusional if they don’t understand it. You are going to have to have a training program.”

Forrester emphasized the intensive learning requirements:

“It forces me to learn new things every day for hours a day going deep. And it’s stuff that I normally would not have gone and read all these academic papers on all of this stuff just for fun, but it is such a fundamental part of what we’re doing, what we have to do in the future.”

Key emerging skills include:

• Vector embeddings understanding – the mathematical foundation of how AI systems process content
• Query fan out analysis – how AI systems expand single queries into multiple related questions
• Multimodal optimization – optimizing for images, video, and voice across platforms
• Cross-platform content strategy – managing presence across Reddit, YouTube, LinkedIn, and other AI training sources

Brand Protection in the AI Era

Perhaps the most concerning development discussed was AI systems’ tendency to misattribute information and conflate identities. Miriam Ellis shared a personal example where her work was attributed to another SEO professional with a similar name:

“My work is being attributed to another SEO called Miriam. Because some person took a YouTube transcript of one of my talks and because my name is not spelled with a Y, it automatically assumed that because I’m talking about local SEO, who’s the other MA that’s known for local SEO? And all of a sudden, my entire life, like my Hawaii references, my Jewish background, all of that is attributed to that poor woman out there.”

Ellis outlined the challenge of “AI brand semantic drift”:

“You have like factual drift. You have intent drift. You have the drift of people on Reddit memeing your brand. You have narrative collapse. Like all of these things are going to be something we have to deal with. And we’re going to have panicked brands coming and going, ‘Clean that up.’ No, I can’t just bury the body in page two of Google search results. Now you have content debt.”

This has led to a new framework for brand management in the AI era, with Ellis describing four distinct categories:

“You need to think about your brand in quadrants, not in I own brand and then I’m going to make SEO demands and PPC demands. There’s what you say about your brand, your known brand… There’s the latent brand, everything that everyone is saying on social media about you… There’s the shadow brand. All the stuff, all the leaks, all those forgotten PDFs… And then from all of these bits, you have the AI narrated brand. It’s now your brand ambassador and for better or for worse.”

• Known brand: Content directly controlled by the organization
• Latent brand: Social media mentions and user-generated content
• Shadow brand: Forgotten documents, legal filings, and historical content
• AI narrated brand: How AI systems describe and represent the brand

Tool Landscape and Investment Surge

The industry is experiencing unprecedented investment in AI-focused tools, with companies like Profound raising $20 million in recent funding rounds. However, experts predict significant consolidation ahead.

Dwayne Forrester predicted major market changes:

“There’s probably going to be another 20 [tools] in the next year and then we’re going to see a metric crap ton of consolidation where all of those ones and twos that made up the companies are just going to drift off because they never got funding.”

The challenge extends beyond tool proliferation to fundamental measurement problems. Mike King noted:

“There’s no connective tissue between there there is no Google search console for ChatGPT and so on so the best you’re going to be able to get at least in the short term is going to be that clickstream data.”

Technical Implementation Challenges

Despite AI advancement, fundamental technical principles remain critical. Miriam Ellis recommended a simple diagnostic approach:

“You don’t need to be technical. Just disable the JavaScript and see if the important stuff is still there. I could nuance this. If you’re a technical SEO, let’s go talk. That’s fine. But if you’re just trying to survive out there, disable the JavaScript and see if all the real information you need on there is on there, like the price of your product, for example.”

Mike King identified vector embeddings as essential knowledge:

“If you don’t understand what a vector embedding is and you don’t really know what you’re doing in this space right now because everything operates on that.”

Measurement and Analytics Evolution

The transformation requires completely new measurement frameworks. King outlined three critical metric categories:

Input Metrics: Passage relevance, bot activity, and traditional rankings as baseline data

Channel Metrics: Performance data from AI platforms, primarily available through third-party tools like Profound

Performance Metrics: Traditional website analytics showing traffic and conversions from AI sources

“There’s no connective tissue between there there is no Google search console for ChatGPT,” King noted, highlighting the measurement challenge facing the industry.

Quality Control and Verification Concerns

Multiple panelists stressed the critical importance of human oversight in AI-driven processes. Dwayne Forrester shared an anecdote about spending 18 hours working with ChatGPT on a video project, only to discover the AI had been simulating work it couldn’t actually perform:

“After about another hour, I said to it, ‘Are you lying to me?’ And it said, ‘Well, that depends.’ And I’m like, ‘What? There is no version of this answer that should start with that depends coming from you.'”

Forrester emphasized the need for constant verification:

“Every single word has to be vetted, every single concept has to be vetted because the basic concepts… the system just conflates those Mike Kings with my reference in SEO and it gives me a link to someone’s company that has nothing to do with the topic.”

He described AI systems in stark terms:

“You’re working with a genius level seven-year-old who has access to humanity’s knowledge but is so interested in saying yes to you that they will lie and not necessarily care about the lie. So that you’re constantly needing to be on top of it.”

Barry Schwartz echoed these concerns with practical examples:

“I’ll be like, ‘That’s wrong.’ And it’s just outright wrong. And it’s like talking to a really confident friend who thinks they know everything, but they know nothing.”

Industry Outlook and Recommendations

Despite challenges, panelists expressed cautious optimism about opportunities for practitioners willing to adapt. Dwayne Forrester noted that the AI association could help elevate industry perception and budgets:

“I need a keyword researcher on my content team. No, you get no more headcount. I need somebody to manage query fan out to determine what content that we should be focusing on moving forward. Is that related to AI? Yes, great. Have two headcount. Like it’s this type of world that I think we’re about to see.”

Mike King provided three key recommendations for the industry:

“SEOs, you need to demand more. Demand more from your tools. Demand more for what the work is that you’re doing… And also you got to demand more from yourselves because again there’s so much that’s happening in this space that you need to learn the nuances of difference.”

“Embrace omnimedia or omni channel content strategy. Again, it’s not just about what’s on your website, it’s what’s across your ecosystem. So you need to be thinking about what are we doing in Reddit, what are we doing on YouTube, what are we doing on LinkedIn Pulse because for whatever reason you publish something there and then you’re in an AI overview, right? Like overnight.”

Miriam Ellis offered practical diagnostic steps:

“You’re not happy with the output you get in an LLM for your brand. Click the thumbs down button and give some feedback as to why it’s bad… Go on perplexity.ai and select because you can do that the Reddit, the social search, disable the web, just look for Reddit and check what people are saying about your brand because that stuff is getting eaten up.”

Dwayne Forrester emphasized the importance of systematic monitoring:

“You should be using the major models in all of the systems… Create a whole bunch of actual prompts that are related to your company, 100, 200. Run those daily, weekly, monthly through the system. Track the results that you’re seeing with dates. Make a matrix for yourself of where you’re showing.”

Immediate Action Items for SEO Professionals:

1. Audit technical foundations: Ensure content accessibility without JavaScript dependency
2. Monitor AI responses: Regularly check how major AI systems describe your brand and business
3. Develop tracking systems: Create matrices to monitor performance across 100+ relevant queries
4. Engage with feedback mechanisms: Use thumbs down buttons and feedback systems when AI provides incorrect information
5. Expand content strategy: Optimize across Reddit, YouTube, LinkedIn, and other platforms that influence AI training

Strategic Recommendations:

• Invest in education: Dedicate significant time to understanding AI fundamentals and emerging concepts
• Build cross-functional relationships: Collaborate with social media, legal, and other departments
• Prepare for consolidation: Evaluate tools carefully as the market matures
• Focus on quality: Emphasize human curation and editorial oversight for all content
• Demand industry recognition: Push for compensation and titles that reflect actual business impact

The Road Ahead

The consensus among industry leaders suggests the next two to three years will be turbulent, with significant opportunities for practitioners who embrace change and substantial risks for those who don’t. Barry Schwartz summed up the industry’s historical resilience:

“The best SEOs continue to add things to their plate… The ones that don’t adapt are the ones that die. And we’ve seen many SEOs with big names over the years that either fell off and are no longer doing SEO.”

Miriam Ellis provided perspective on the cyclical nature of industry transformation:

“I’m old enough to know everything that’s old is new again… It’s just not the same game. And now you’re running into new frictions with new teams.”

The transformation represents more than technological change—it’s a fundamental shift in how information is discovered, processed, and valued in the digital economy. For SEO practitioners, success will depend on evolving from tactical implementers to strategic advisors who understand both human behavior and AI system operations.

As Mike King noted about the fundamental shift in channel dynamics:

“Everything is fundamentally different. The channel is different. The user behavior is different. The expectations of what we do in order for us to achieve something in this channel has dramatically changed.”

As the industry navigates this transition, one thing remains clear: the days of checklist-based SEO are ending, replaced by a discipline requiring deep technical knowledge, cross-functional collaboration, and continuous adaptation to rapidly evolving AI capabilities.

This report is based on insights from a recent industry panel featuring leading SEO practitioners and industry observers, reflecting current challenges and opportunities in the evolving search landscape.