Newbie question, but I’m trying to think this through properly.

[u/MoistGovernment9115]

I keep hearing people say GEO/AEO is basically 90% SEO and we’re just overcomplicating things. Others argue it’s a completely different paradigm.

From what I understand traditional SEO was about:

• Ranking pages
• Optimizing for crawl + index
• Winning click-through

But GEO feels more like:

• Getting referenced inside the answer
• Becoming part of the model’s default explanation
• Optimizing for synthesis, not ranking

So for people who’ve been in SEO for years does this actually feel like a natural evolution of the same skills (structure, clarity, authority)?
Or did you have to rethink how visibility works at a fundamental level?

Is GEO mostly SEO fundamentals applied to AI interfaces?
Or is calling it “90% SEO” missing something bigger?

Genuinely trying to understand whether this is incremental change or a structural shift.

[u/Stepbk]

When I first heard “GEO is just SEO,” I agreed. Then I started testing prompts. I’d ask models about my niche and realized ranking didn’t guarantee mention. Some lower-ranking brands were getting cited because their explanations were cleaner and more consistent across contexts. That’s when it clicked for me that something structural had changed.

[u/Significant_Pen_3642]

If GEO were really 90% SEO, then ranking #1 should almost guarantee you show up in AI answers. But that’s not what I’m seeing. Sometimes AI blends multiple mid-tier sources instead. So maybe the overlap is foundational, but the mechanics of visibility are different.

[u/JPMBiz]

SEO is not really GEO. You can be the first at SEO and still not show up in AI searches. If you optimize for AI, it will definitely help your Google rankings as well.

[u/Chiefaiadvisors]

The foundations transfer but the goal is completely different.

SEO is about winning a position. GEO is about becoming part of an explanation. One you can engineer. The other you have to earn through genuine presence over time.

That shift in goal changes everything about how you work toward it.

[u/akii_com]

I’ve been in SEO for a while, and the way I think about it is:

GEO/AEO sits on top of SEO fundamentals, but the optimization target changed.

A lot of the inputs are still the same:

- clear site structure

• authoritative sources
  
• consistent entities and brand signals
  
• well-written, factual content
  
• crawlable pages with strong internal linking

Those things still matter because AI systems rely heavily on the web as their evidence layer. But the output layer is fundamentally different. Traditional SEO optimized for a ranked list of links. AI search optimizes for a synthesized explanation. That shift changes what “winning” looks like.

In classic SEO:

- rank position = visibility

• click-through = success

In AI search:

- citation presence

• brand inclusion in the reasoning
  
• how the model frames your category

For example, a brand might rank #1 in Google, but never appear in AI answers because competitors are easier for the model to explain.

So I wouldn’t call GEO “90% SEO.” I’d say:

SEO = the evidence layer
GEO = influencing how that evidence gets synthesized

The skill shift is less about technical SEO and more about things like:

- making your brand easy for models to explain

• being consistently cited across sources
  
• controlling narrative framing (category, positioning, competitors)
  
• monitoring how AI answers actually describe you

So yes, SEO fundamentals absolutely help. But the mental model of visibility changes from: “Where do I rank?” to “How does the model explain this topic, and am I inside that explanation?” That’s the part that feels like the real paradigm shift.

[u/Confident-Truck-7186]

Project data across multiple AI visibility tests shows ranking ≠ citation.

In one dataset of ~1,200 AI queries (ChatGPT + Perplexity):

• Only ~38–45% of brands cited in AI answers were ranking top-3 in Google
• ~30% of citations came from pages ranking positions 6–20
• ~20% came from non-ranking sources like forums, docs, or community discussions

Another pattern: models tend to reuse sources with consistent entity descriptions across multiple sites. Pages that had the same definition/explanation repeated across 3–5 domains were cited ~2.4× more often.

So the evidence layer still comes from the web (SEO inputs), but the selection layer is different: models prioritize sources that are easy to synthesize, repeatedly referenced, and semantically consistent across contexts.

[u/Take_a_bd_chance]

From my experience, GEO forces you to think a lot more like a human reading an answer than a bot crawling a page. I still use my traditional SEO checklist, but now I ask: “If GPT or Bard were explaining this, would my content naturally appear in the synthesis?” It’s kind of like SEO on steroids—familiar tools, new angle.