Four SEO practitioners sat on a panel at WordCamp Europe and spent an hour disagreeing about whether AI fundamentally changes SEO or simply accelerates what was already happening. But underneath the disagreement, they landed on the same four points every time.
If you run a website, a SaaS, or any content-driven business, those four points are worth your attention.
Who Was on the Panel
- Alex Moss, Principal SEO at Yoast SEO
- Pam Aungst Cronin, owner of Pam Ann Marketing and Stealth Search and Analytics
- Jovana Smoljanovic Tucakov, Content and SEO Lead at Melograno Ventures
- David Cuesta, founder and CEO of AMDSEO.es
- Host: Kacper Bartoszak
The backdrop was Google’s announcement at Google I/O that its search box is transitioning toward an “intelligent Search box” that moves fluidly into AI Mode and AI Overviews. The host asked whether that changes anything for the WordPress community and for SEO practitioners specifically.
Point 1: Generic content is already losing
Alex Moss opened with the clearest statement of the session. If you’re debating how aggressively to scale AI-generated content, you’ve already asked the wrong question.
“Scaling content is a really good example. If you’re questioning how much to scale, you shouldn’t be doing it. And if anything, you should be just doing, as Google say, unique quality, non-commodity content intended for humans. Agents know that they’re not the end user, they’re just a gateway to the end user, which is the human. So it still has to adhere to some of those rules.”
Google’s Danny Sullivan has made similar statements about commodity content: generic content that lacks a unique human viewpoint or any other value add is increasingly a poor long-term bet. David Cuesta framed it slightly differently, saying AI search has raised the bar on what kind of content will succeed. The two views are compatible: the floor for acceptable content is rising, and the ceiling for differentiated content is rising faster.

Point 2: SEO and marketing can no longer operate separately
Jovana Smoljanovic Tucakov pushed the panel toward a structural observation about how SEO teams are organized. The siloed SEO specialist who optimizes in isolation from the rest of the business is operating with an outdated model.
“I feel that before, SEO teams and SEO specialists were really looking like niche things and looking to SEO like just one part of the puzzle and they were not looking the entire picture of marketing. And today, I believe that in order to do good SEO, GEO or whatever and be included in AI generated answers, you need to look at SEO and marketing as a whole. So you need to approach it as like brand strategy, product marketing, SEO tactics we were already using, but just like upgraded on much higher level.”
Pam Aungst Cronin agreed and added a precise way to think about where SEO fits now. She described GEO (generative engine optimization) as a layer built on top of traditional SEO, not a replacement for it. The structural work of technical SEO and content still matters. The new layer is brand.
“Brand is the new backlink. That is what really you need to think about. Branding is just such a bigger thing, and it’s about awareness building. That’s what you need to do to get the AIs to recommend your brand.”
The logic is straightforward. When AI systems synthesize answers and surface citations, they’re not counting clicks. They’re drawing on which brands and sources are consistently recognized as credible across many signals. Chasing the citation matters more than chasing the click.
Point 3: AI systems need less ambiguity, not more content
When the discussion turned to practical tactics, the panel converged on a theme: make it easier for AI to understand your business accurately.
Alex Moss focused on three specific areas:
- Structured data: explicit markup that tells AI systems what a page contains
- Entities: clear identification of who and what your business is
- Data integrity: how clearly information is presented, so AI systems need less interpretation work
The underlying concept is disambiguation. Every element of a page, from semantic HTML to headings to site architecture, should reduce ambiguity. The less inference an AI system has to make, the less likely it is to produce an inaccurate answer about your business.
Jovana Smoljanovic Tucakov applied this to product positioning specifically. Strategic pages should clearly state what a product does, who it serves, what problems it solves, and why the claims are credible. She also stressed consistency: the same signals should appear across your website, PR, social profiles, and any external mentions.
David Cuesta addressed smaller businesses directly. Established brands already have recognition. Smaller operators need to work harder at differentiation. His recommendations were local visibility, social amplification, unique content, and building something competitors can’t easily copy.

Point 4: First-hand experience is the signal AI can’t fake
Google added a second “E” to its E-E-A-T framework (Experience, Expertise, Authoritativeness, Trustworthiness), and Pam Aungst Cronin argued that this addition signals something important about where AI search is heading.
Her point was blunt: adding an author bio is not enough. Content needs to contain firsthand observations, projects, events, and examples that demonstrate how expertise was actually acquired. That is where businesses can create information that AI systems cannot easily reproduce.
AI can generate content. It cannot generate genuine personal experience.
The panel also addressed the tactics question directly. Jovana Smoljanovic Tucakov said businesses should stop looking for ways to trick search systems and focus on quality, products, users, and marketing. Pam Aungst Cronin used Reddit as a concrete example: Reddit ranks well not because it found a loophole, but because it contains authentic human experiences that AI systems treat as original source material.
David Cuesta was slightly more open to promotional activity. He said public relations campaigns can still build awareness and visibility in AI results, even when the resulting links are nofollow.
“Many times it’s all links that are nofollow, but that they are working very good positioning in the AI.”
What the panel said about the next 10 years
The most speculative part of the session covered where search goes long-term. Pam Aungst Cronin predicted that AI agents will increasingly handle research, comparisons, and transactions on behalf of users, turning websites into interfaces for software rather than destinations for people. Alex Moss argued the shift depends on context: routine purchases may get delegated to agents, but high-stakes decisions involving significant money or personal preference will likely still involve a human. David Cuesta suggested agents will handle more scheduling and coordination even when humans retain final authority.
The panel’s honest conclusion: nobody knows what search looks like in ten years.
The four things to take away
The panel’s disagreements about velocity and degree shouldn’t obscure the consensus underneath. AI search increasingly rewards:
- Clarity: structured data, unambiguous entities, consistent signals across every surface
- Brand: recognition that earns citations, not just clicks
- Uniqueness: content that can’t be reproduced by a model trained on existing web data
- Demonstrated experience: firsthand knowledge that no AI was present to acquire
These aren’t new principles. They’re the principles that have always separated durable SEO work from tactics that expire when the algorithm changes. The difference now is that AI search is making the gap between the two harder to ignore.

