September 14, 2025
|8 minute read
At Google’s highly anticipated Search Central Live Deep Dive Asia Pacific event, a clear message emerged for the thousands of SEO professionals in attendance: the frenzy around creating a separate strategy for Generative Engine Optimization (GEO) is misguided.
As Google’s Head of Search, Liz Reid [1], has often stated, “Search is never a solved problem.” And the industry’s recent “acronym anxiety” is proof of that constant evolution.
The rise of terms like GEO and AEO has caused widespread concern that the core tenets of SEO are now obsolete. But Google’s experts used the Bangkok stage to systematically dismantle this notion.
In a packed keynote session, Cherry Prommawin [4] of Google Search Relations addressed the issue head-on.
We see the conversation and the anxiety. But we don’t think SEO for GEO and AEO needs a new framework. It’s the same infrastructure. The same principles of helpfulness and authority apply.
This critical point was echoed in a more technical session led by veteran Googler Gary Illyes [4]. He explained that from an engineering perspective, there is no separate system for AI-driven results.
“Think of it as one unified system with different ways of displaying information. Both AI-driven tools and classic Search services share a single, unified infrastructure. The signals that feed into our ranking systems are the same signals that help inform AI Overviews.”
The official guidance from Google is that the principles that have long defined good SEO are not only still relevant but are now more crucial than ever for achieving visibility in an AI-driven search landscape.
To understand why this clarification from Google is so significant, it’s important to understand the trend that sparked the panic.
The term Generative Engine Optimization (GEO) was coined to describe the strategic practice of optimizing content not just to rank, but to be actively cited, synthesized, and featured within Google’s AI-generated answers.
This represents a fundamental mindset shift. For two decades, SEO was about securing a top position on a list of ten blue links.
GEO is about becoming the raw material for a direct, synthesized answer.
This creates a “winner-takes-most” dynamic that is far more punishing than traditional SERPs. In the old model, ranking in positions two through ten still delivered significant traffic and value.
In an AI-Overview, if your site is not cited as a source, it may receive no visibility at all for that query, effectively becoming invisible.
This focus is a direct response to the explosive growth of AI Overviews (AIOs) and their very real impact on the SERP ecosystem.
According to one study [2], AI Overviews now appear in over 50% of all English-language search results, a dramatic increase from just 25% ten months prior.
Even more concerning for site owners, research suggests the presence of an AIO can cause a potential 18% to 64% reduction in organic click-through rates, depending on the query’s nature [3].
This data highlights a critical challenge: when Google provides a direct answer, the user’s need to click through to a website diminishes significantly.
While this threat to traffic is real, Google’s guidance insists the solution isn’t a radical new set of tactics, but a more profound execution of existing ones.
Google’s advice is not surprising when viewed through the lens of its history. The pivot to AI-driven answers is the logical endpoint of a two-decade-long journey away from simple keyword matching and toward a deep understanding of user intent.
This trajectory is visible in Google’s landmark algorithm updates:
AI Overviews are the culmination of this journey. As Google Search Advocate John Mueller [5] commented in a recent office-hours hangout,
“The underpinnings of what Google has long advised carry across to these new experiences. If you’ve been focused on creating truly helpful, reliable content, you are already on the right path.”
The most powerful way for SEO professionals to conceptualize this challenge is to look at a complex discipline we have managed for years: International SEO.
It provides a perfect blueprint for how to integrate a new set of signals into a single, cohesive strategy without inventing a new silo.
When a website needs to serve different content to users in different countries, we do not invent a new practice called “International Engine Optimization” (IEO).
Instead, we apply foundational SEO principles through an integrated, two-pillar approach:
This same integrated framework applies directly to optimizing for generative AI.
The unifying principle is a focus on user need.
Structuring a page with a concise answer at the top might seem like “optimizing for bots,” but it is fundamentally about serving the human user who is now using an AI-powered tool to get a fast answer.
Therefore, “GEO” is not a separate strategy; it is an evolution of the “people-first” principle.
Based on this framework, SEO professionals should double down on these core best practices. They are no longer just best practices; they are essential for AI-era visibility.
A single, well-optimized page is no longer enough.
Implement the Hub-and-Spoke Model, develop central “pillar” pages for your core topics, and surround them with clusters of “spoke” content that address every conceivable user question.
Master your internal linking to create a logical, machine-readable structure that signals a deep well of knowledge.
For any given topic, create content that satisfies informational, commercial, and transactional intent.
Google’s systems will inevitably rely more heavily on E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) to verify and prioritize information.
Publish genuine case studies and first-person accounts to show Experience. Create detailed author bios with credentials and use Person Schema to prove Expertise.
Seek citations and links from other respected sites and publish original research to build Authoritativeness. Make contact information and policies easy to find, and ensure your site is secure to build Trustworthiness.
This is how you speak the AI’s native language. Go beyond basic Article and FAQ Schema. Implement Organization, Person, Product (with review and aggregateRating properties), and BreadcrumbList Schema.
Use the JSON-LD format and nest your Schema types to create a rich, interconnected graph of information that Google’s systems can ingest with near-perfect accuracy.
Clicks from AIOs are high-intent.
A poor landing page experience is a fatal flaw. As Cherry Prommawin [6] noted, your crawl budget is a product of crawl rate and demand.
Broken links, 5XX errors, and slow server responses directly hinder Google’s ability to crawl and index your best content efficiently.
Prioritize fixing these issues in Search Console. User journeys are no longer just text-based. Optimize for multiple modalities by providing descriptive alt text for all images, full transcripts for videos and podcasts, and using conversational language that translates well to voice search.
A page that’s easy for a human to skim is also easy for an AI to parse. Obsess over Core Web Vitals (LCP, INP, CLS)*.
Optimize your information architecture with clear headings and tables of contents. Reduce cognitive load by avoiding intrusive pop-ups and complex layouts, and add visual callouts like blockquotes.
* LCP, INP, CLS: Largest Contentful Paint (LCP), Interaction to Next Paint (INP), Cumulative Layout Shift (CLS)
The emergence of AI Overviews represents a significant shift in the search landscape, and the threat it poses to organic traffic is not to be underestimated.
However, the path forward does not lie in chasing a new, secret playbook for “GEO.”
According to Google’s experts, the solution is a renewed, intensified, and more disciplined focus on the user-centric principles that have always defined a successful and sustainable SEO strategy.
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