I’ve been doing SEO for 12 years. I know Google inside out. But AI search feels like a different game entirely.
What’s confusing me:
Some clients rank well in Google but never appear in AI answers. Others barely rank in Google but get mentioned by ChatGPT constantly.
My observations:
What I need to understand:
Chris, you’ve identified the core tension. They’re related but distinct disciplines.
The fundamental difference:
Google: Ranks pages based on relevance + authority signals AI: Synthesizes answers from multiple sources it trusts
Signal comparison:
| Signal | Google Importance | AI Importance |
|---|---|---|
| Backlinks | Very High | Low-Medium |
| Keyword density | Medium | Low |
| Domain authority | High | Medium |
| Content freshness | Medium | Very High |
| Brand mentions | Low | High |
| Structured data | Medium | High |
| Content comprehensiveness | High | Very High |
| Third-party citations | Medium | Very High |
The key insight:
Google asks: “Which page deserves to rank #1?” AI asks: “What sources should I cite when answering this question?”
These are different questions with different answers.
The third-party citations point is interesting. So instead of building links, I should focus on getting mentioned?
What’s the practical difference between a backlink and a brand mention for AI?
Links vs. Mentions:
Backlink (Traditional SEO):
Brand mention (AI):
Example:
A press release with a backlink but generic text: helps Google A Forbes article that says “[Brand] is the leading solution for [use case]”: helps AI
The strategic shift:
Instead of “get me a backlink from Forbes,” think “get Forbes to write favorably about us in context.”
The mention teaches AI about you. The link taught Google about you.
Content strategy differences between AI and Google:
Google-optimized content:
AI-optimized content:
What works for both:
The practical approach:
We now create content with dual optimization:
Technical SEO differences:
What still matters for both:
What matters MORE for AI:
What matters LESS for AI:
New technical elements for AI:
Agency perspective on managing both:
How we structure services:
Core SEO (still essential):
AI Visibility (new layer):
Resource allocation (for a typical client):
Why not 50/50:
Google still drives 90%+ of search traffic. But AI is growing fast and has higher conversion rates. We’re gradually shifting as the market shifts.
Data perspective on AI vs. Google performance:
Our analysis of 500+ URLs:
| Metric | Correlation with Google Rankings | Correlation with AI Citations |
|---|---|---|
| Backlinks | 0.72 | 0.21 |
| Domain Authority | 0.68 | 0.28 |
| Content length | 0.41 | 0.35 |
| Content freshness | 0.32 | 0.67 |
| Brand mentions | 0.25 | 0.71 |
| Structured data | 0.38 | 0.54 |
| Keyword density | 0.45 | 0.18 |
Key insights:
These are genuinely different ranking factors.
Writer’s perspective on the difference:
Writing for Google:
Writing for AI:
How I write now:
I write for humans first (which serves AI well), then add SEO elements for Google.
The “write for humans” advice was always right, but it’s now literally the AI strategy. AI extracts content that sounds human and authoritative.
Measurement differences:
Google metrics:
AI metrics:
The challenge:
Google Search Console shows your Google performance. There’s no “AI Search Console.”
You need tools like Am I Cited to track AI visibility. It’s a different measurement infrastructure entirely.
Our approach:
Weekly AI visibility reports alongside weekly SEO reports. Different dashboards, different KPIs, different optimization strategies.
Industry perspective on where this is heading:
Current state:
But:
Prediction:
In 3 years:
Strategic implication:
You need both, but for different reasons:
The skills overlap but the emphasis differs.
This thread clarified the landscape. Here’s my new mental model:
What transfers from SEO to AI:
What’s different for AI:
My updated playbook:
Foundation (serves both):
Google-specific layer:
AI-specific layer:
Resource allocation shift:
Moving from 100% traditional SEO to:
Will likely shift further as AI traffic grows.
Thanks everyone for helping me update a 12-year-old playbook.
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