GEO echoes early SEO as brands race for AI visibility

Google’s AI Overviews are now live in U.S. search results after debuting as Search Generative Experience at Google I/O 2023, and the shift has pushed brand mentions inside synthesized answers onto the core marketing agenda. AI visibility is moving through the same messy phase that shaped early SEO, but the rules are not identical. Many teams are assuming an existing SEO program will automatically carry them into AI-generated results, when the new systems reward a wider set of signals and a different kind of authority.

The current market looks like early SEO, but the stakes are higher

The early-SEO comparison captures the mood: loose tactics, unclear metrics, and a land-grab mentality. In the first wave of search optimization, teams found shortcuts, scaled them fast, and later watched those shortcuts lose power or draw penalties. GEO is now entering a similar phase, but the lesson is not that anything goes. The first advantage belongs to brands that move early without building on sand.

Google still anchors the market, with more than 90% search market share even as AI search usage grows, according to BrightEdge. ChatGPT grew 21% in the last month, while Perplexity and Gemini remain about one-tenth of ChatGPT’s size, BrightEdge found. Brands are no longer optimizing for one discovery surface, but for a stack of surfaces that behave differently.

Why SEO helps, and why it stops short

MarTech argues that good SEO helps, but it does not maximize visibility in AI answers because the systems and incentives are different. Traditional search optimization was built around ranking links; AI search assembles answers, often pulling from a broader and less predictable set of signals. That means a page can be technically well optimized and still miss the synthesis layer if the brand has weak external authority, thin community proof, or inconsistent topical coverage.

Semrush calls AI Overviews one of the biggest changes in search since featured snippets, and the comparison is apt because both features changed how users encounter answers. But AI Overviews go further by reducing the prominence of the blue-link path and rewarding brands that can be summarized cleanly by the system. In practice, that shifts attention away from one-page keyword wins and toward cross-site consistency, topical clarity, and enough real-world brand evidence for the model to trust.

The lesson from early SEO is not speed alone, but durability

The early SEO analogy is also a warning about durability. Tactics that once worked well eventually got weaker or became liabilities when search engines changed the rules. GEO is headed down the same road if teams treat current AI behavior as a permanent loophole.

The strongest GEO programs are not built around hacks. They are built around content that can survive platform evolution, policy changes, and model updates. MarTech argues that the goal is not to game a current algorithm but to earn durable visibility through credible content, trustworthy signals, and strategic consistency. The market is still relatively open, which creates room for first movers, but that window will narrow as more brands copy the same playbook.

What durable GEO actually looks like

The emerging playbook is broader than content production. AI visibility is becoming a C-suite mandate because discovery is shifting from clicks to conversations, MarTech argues, and that change pulls in search, brand, PR, and community teams at once. A brand that publishes useful content but neglects third-party credibility, structured data, and public discussion will struggle to look authoritative when an answer engine compresses the field.

A practical GEO program usually includes:

• Structured content that makes products, categories, and use cases easy to parse.
• Consistent brand naming and messaging across owned and earned channels.
• Public proof points that appear outside the company site, including reviews, discussions, and references.
• Internal alignment between SEO, communications, and product marketing so the same entity signals appear everywhere.
• Ongoing monitoring of how AI systems mention the brand, not just where the website ranks.

Patagonia and Garmin fit this model in MarTech’s examples. Neither brand appears to win because of one clever page or one search trick. They benefit from steady, structured visibility signals that make the brand easy to recognize and hard to confuse.

Community signals now matter more than many SEO teams expected

One of the biggest changes in AI search is the rising importance of forums, reviews, and authentic user conversations. Those sources are increasingly treated as authority signals because they reflect how real people talk about products, categories, and trade-offs. That creates a sharper lesson for marketers used to controlling the message: visibility is no longer determined only by what the brand says about itself.

Ahrefs analyzed 75,000 brands to identify factors most likely to influence brand mentions in AI Overviews, then expanded the work to ChatGPT, AI Mode, and AI Overviews. The pattern is not a single trick or channel, but recognizable signals that recur across surfaces. The brand has to show up as a real entity in many places, not just as a well-optimized website.

The buying landscape is widening, not replacing itself

AI visibility is additive for marketing teams. Google still matters most because of its scale, but ChatGPT, Perplexity, and Gemini are now part of the discovery path, and usage patterns are shifting fast enough to reward teams that build for portability. A strategy designed only for rankings will miss the moment where a model needs a concise, trusted answer rather than a list of pages.