SEO vs AEO: What Actually Changes on the Page
One of the hottest debates in marketing right now? What are we calling the “new SEO?”
Should it be AEO, GEO, AI SEO? Or just AI Search Optimization?
Regardless of which side you land on, what’s fascinating is just how little attention is being given to the actual practice of optimizing for LLMs. Maybe our obsession with the label is because few teams are really sure how to approach—let alone win—AEO or GEO in the first place.
Yes, we know in a spiritual sense that the mission is different than it was in the SEO era. LLMs are surfacing answers, not just ranking blue links.
But what is the practical, tactical difference between the “before times” (when we created or updated a page specifically for Google’s algorithm) and right now (when it’s all about wooing LLMs as they build customized answers)?
There are plenty of people who question whether there really IS a difference.
After all, in the last two years, zero-click answers were already common on Google’s SERP, and SEOs had begun adapting their strategies. At some point, you can’t be blamed for wondering:
Isn’t optimizing for AI answers basically the same as SEO?
How much is actually changing on the page?
These are totally reasonable questions. And for a few years, the industry’s default answer was: not much.
Why ranking well for SEO no longer guarantees AEO inclusion
Early conversations around AEO assumed that if you ranked well in Google, you’d naturally show up in AI answers too. But newer research shows that the sources cited by major AI systems often don’t align with Google’s top-ranking results for the same queries. In fact, they only overlap about 5-20 percent of the time.
At the same time, user behavior is shifting. It’s become clear that people aren’t just relying on Google to feed them rank-ordered pages.
Bain & Company found that 80 percent of searchers now rely on AI-generated summaries for at least 40 percent of their searches, and roughly 60 percent of searches end without a click to another site. The discovery layer is changing quickly, and the mechanics of how answers are assembled are changing with it.
That definitely doesn’t mean SEO isn’t important anymore—its just changing when it matters. People still very much use search engines, but they’re more likely to type in a branded search after they know they’re interested in your company and want specific information.
All the shifts to search mean that the engines deciding what gets surfaced are no longer identical. That has real implications for marketers on how we should write, structure, optimize and prioritize content.
In practice, the differences show up right on the website page. The structure, the headings, the way paragraphs are written, even the role of a blog versus a core page all start to change.
But Didn’t SEO Teams Always Optimize This Way?
None of the “new” tactics below will be completely revolutionary to seasoned SEO teams. In fact, many of them emerged in late-stage SEO as best practices: tighter intros, cleaner headings, stronger canonical pages.
What’s changed is that these tactics have moved from “nice to have” to actual structural requirements for AEO/GEO. Where as before you could probably still rank well without perfectly compressible paragraphs or clean answer modules—now, you need them to get surfaced at all.
Here’s how to do it right.
7 Specific Ways to Optimize a Page of LLMs
Here’s how writers, editors, and marketers need to change tactics to get surfaced in AI search environments:
1. Shift the intro from setup to answer
Traditional SEO introductions often exist to set context and get people scrolling. They introduce the topic, build tension, and promise value later. But an LLM doesn’t need a warm-up, it just needs an answer. An AEO-optimized intro answers the core question of the page within the first few sentences, names specific entities, and provides enough context to stand on its own.
2. Make headings mirror real questions, not just keywords
SEO-era headings were usually built around keyword variations because they helped with rankings and scanability. But LLM prompts are conversational and question-based.
When a heading mirrors a real user prompt and is followed by a direct answer, it creates a clean, chunkable section that a model can easily retrieve. Chunkable content is structured so that a single section—heading plus a short answer—can stand on its own and be lifted directly into an AI response without needing much context or rewriting.
Over time, this changes the feel of a site. Instead of reading like a collection of loosely related blog posts, it starts to look more like a structured knowledge base that’s easy for both humans and AI systems to navigate.
3. Feature paragraphs as standalone answers
If headings create chunkable sections, the paragraphs beneath them need to function as chunkable answer units. SEO writing often prioritizes narrative flow. Paragraphs assume the reader has context from earlier sections. LLMs don’t make that assumption. When a paragraph is retrieved, it may be separated entirely from the rest of the page.
AEO-optimized paragraphs name the subject, define it, and explain its role in a single, contained thought. A helpful mental model is this: if a paragraph were copied on its own into an AI answer, would it still make sense to someone who had never seen the rest of the page? If the answer is no, it probably isn’t very compressible.
4. Give lists and comparisons consistent internal logic
Listicles have long been a staple of SEO, but they were often written in uneven, marketing-heavy ways. One item might describe features, another might talk about pricing, and a third might focus on use cases.
In an AEO context, lists work best when each entry follows the same structure and answers the same implicit question—best for whom, best for what, or best under which conditions. That consistency makes the list more chunkable and easier for models to reuse without rewriting or reinterpreting it.
5. Give definitions not slogans
SEO copy has historically tolerated vague, promotional language. Phrases like “leading solution” or “powerful platform” didn’t necessarily hurt rankings. But LLMs rely heavily on definitional clarity. They need to know what something is, what category it belongs to, and what problem it solves. When a page clearly defines a concept or product, it becomes much easier for the model to place it correctly inside an answer. Precision beats persuasion in an AI-driven environment.
6. Make FAQs into answer modules, not long-tail padding
In traditional SEO, FAQs were often added for keyword coverage and treated as an afterthought. In an AEO context, they become some of the most valuable real estate on the page. Each question-and-answer pair should function as a self-contained answer unit, with the first sentence doing most of the work. When written well, an FAQ section becomes a set of ready-made answer blocks that AI systems can lift directly into responses (check out mine below as an example).
7. Move from blogs to canonical answer pages
For years, most content strategies were blog-heavy because blogs drove rankings and traffic. But AI systems tend to prefer stable, definitive, evergreen pages that clearly answer foundational questions. Pages like “What is X?”, “How X works,” or “X vs. Y” are easier for models to trust, cite, and reuse.
That doesn’t mean brands can’t win here. In many cases, the brand that provides the clearest, most authoritative explanation becomes the source the model relies on—and gets cited, linked, or mentioned in the answer.
Blogs still matter, but their role shifts. Instead of serving as the primary sources models quote, they become a supporting layer—expanding topical authority, exploring new ideas, and feeding into stronger, more canonical answer pages over time.
The Test: Will your brand or page show up as an LLM answer?
When we audit and optimize content at Masthead, our work usually comes back to two questions:
If an LLM copied just one paragraph from this page, would it clearly answer a user’s question?
If this topic is important to the business, do we have a definitive page for it, or just a collection of loosely related blog posts?
Those two questions alone can reshape an entire content and AEO strategy. They force you to look beyond rankings and traffic and ask a more fundamental question: are we actually building the kinds of pages AI systems want to use as answers?
AEO isn’t SEO with a new name. It reflects a deeper shift in how information is retrieved, trusted, and reused. But one fundamental thing hasn’t changed. Whether it’s Google or an LLM assembling an answer, the brands that get served up are the ones that understand what users are really asking—and respond with clear, useful, trustworthy information.
That’s how to win in the new AEO area.
If you need more specific guidance for your brand, I’m here for questions. But here are a few that may be on your mind after reading this piece.
Frequently Asked Questions about Optimizing for AEO
Is AEO replacing SEO?
No. AEO builds on traditional SEO, but focuses on making content easier for AI systems to retrieve and use in generated answers. SEO is still critical for rankings and traffic, while AEO helps brands appear directly inside AI responses.
How is AEO different from traditional SEO?
Traditional SEO focuses on ranking entire pages in search results. AEO focuses on making specific sections of a page clear, structured, and compressible so they can be included in AI-generated answers.
Can a page rank in Google but not appear in AI answers?
Yes. Research shows that many sources cited by large language models do not overlap with Google’s top-ranking results by much (only around 5-20 percent). A page can perform well in traditional search but still be ignored by AI systems if it isn’t clear and compressible as an answer.
Are blog posts still useful for AEO?
Yes, but their role changes. Canonical, evergreen pages are more likely to be cited directly in AI-generated answers because they clearly define concepts and provide structured explanations.
What is the ideal length and structure for an AEO-optimized FAQ answer?
The ideal FAQ answer is usually 40–90 words, or about two to four sentences. The first sentence should directly answer the question, the second should clarify, and a third can provide an example.
Who is responsible for optimizing content for AEO?
AEO is usually a shared responsibility across content, search, and product marketing teams. Many organizations also work with specialized partners, like Masthead, to set the AEO strategy and handle the actual optimization work.
Will mentioning my brand prevent a page from being cited in AI answers?
No. AI systems regularly cite brand-owned pages when those pages clearly define a concept, product, or service. Clear, neutral, and informative content is far more likely to be used than overly promotional language.
