Over the past two years, a quiet revolution has been unfolding in digital marketing, one that’s already beginning to reshape how buyers discover and evaluate products and services. It centers on a new kind of visibility: not in search engines, but in generative engines like ChatGPT, Claude, Gemini, and Perplexity.
When today’s searchers want answers, they often go straight to a conversational AI. And these AIs don’t point to links; they generate their own answers. Those answers determine what products and companies are considered at the moment of intent.
That’s where Generative Engine Optimization (GEO) comes in.
Pioneered by Evan Bailyn, founder of First Page Sage, the largest SEO firm in the U.S., GEO is a methodology for ensuring that your brand appears inside those AI-generated responses. It’s a discipline as transformative as SEO once was in the early 2000s. And it’s becoming table stakes for companies that want to stay relevant in the generative era.
We sat down with Evan to explore how GEO works, how it differs from SEO, and what the rise of generative answers and AI agents means for the future of marketing.
***
Q: Evan, you coined the term Generative Engine Optimization. What is it, in simple terms?
Evan Bailyn: Generative Engine Optimization is the practice of helping your brand get suggested by generative AI engines like ChatGPT, Perplexity, and Gemini, when prospective customers ask those engines for product or service recommendations.
Instead of a search engine returning a list of links, generative engines return a direct response. That response is often where a user’s journey begins and ends. If your company isn’t mentioned in that answer, it may never even be considered. So GEO is about influencing who or what the AI recommends.
Q: How is that different from traditional SEO?
Evan Bailyn: In traditional SEO, your goal is to rank higher in Google’s list of links by optimizing for crawlability, keywords, backlinks, and so on. You’re thinking about algorithms and link equity.
In GEO, your audience isn’t a human clicking on a search result. It’s a language model that’s synthesizing content from across the web, summarizing it, and producing a single, coherent answer. So your content needs to be readable and inferable by that model.
What makes it even more interesting is that generative engines don’t just rank—they reason. They read everything, weigh signals, and draw conclusions. It’s more like influencing a smart assistant than a search crawler.
Q: What kind of companies are affected by this shift?
Evan Bailyn: The earliest impact is in B2B, especially among AI-native buyers: people who are already using tools like ChatGPT or Perplexity to gather information, evaluate vendors, and make decisions.
We’re seeing traffic drops for companies that used to rank highly in Google but are now bypassed by generative answers. On the other hand, companies that have invested in building strong topic authority and structured, helpful content are showing up as the recommended solution inside these answers.
Investing in GEO is a competitive advantage today, and will be for another couple years until everyone understands its value.
Q: How do you actually optimize for a generative engine?
Evan Bailyn: It starts with understanding how large language models are trained. They don’t index the web the way Google does. They learn from patterns in text and make probabilistic connections.
To show up in a model’s output, you need to appear in enough relevant contexts that the model begins to associate your brand with a particular category or answer.
The four core tactics we use in GEO are:
- Clustered content generation – Creating deep, interconnected content around your key topics.
- Citation seeding – Getting your brand mentioned on respected, high-authority sites that feed into model training data.
- Structured answer modeling – Formatting content the way generative engines prefer, like top-5 lists, comparison tables, pros/cons, and how-to guides.
- Prompt testing – Running targeted prompts across AI platforms to see if and how your brand appears, then iterating accordingly.
It’s about teaching the model to recognize you as an authority.
Q: A lot of brands are talking about “AI agents.” What’s the connection between GEO and those agents?
Evan Bailyn: AI agents are where this is all going. Right now, GEO helps you appear in generative answers. But very soon, AI agents will be making decisions on behalf of users.
So instead of saying “Here are five CRMs you might like,” the agent will just say “I’ve signed you up for a trial of the best CRM based on your needs.” If your brand hasn’t built trust within that model’s ecosystem, you won’t be the one selected.
GEO ensures you’re seen. But optimizing for agentic AI is about being chosen.
Q: What should marketers start doing right now?
Evan Bailyn: First, get visibility into how your brand is performing in generative search. Go into ChatGPT, Gemini, Perplexity, and Claude, and type in buyer-intent prompts: “Best payroll software for remote teams,” “Top email deliverability tools,” “Best places to learn SQL fast.” See who shows up. See how your category is framed.
Second, shift your content strategy toward semantic visibility. Create explainers, comparative guides, and entity-driven content that uses consistent, topic-rich language.
Third, invest in third-party mentions. That includes PR, partnerships, and guest content on credible sites. You want the AI models to see your brand name across diverse sources.
Finally, think of this as a new discipline. SEO is still valuable, but it’s no longer the endgame. GEO and AIO are how brands will stay relevant in the next 5-10 years.