The question on everyone's mind: is SEO the same as AEO? We think a distinction is important because SEO was built on how traditional search engines operated - not AI.
Growth marketer and B2B demand specialist with expertise in AI search optimisation - I've worked with 50+ firms, scaled some to 8-figure ARR, and managed $400k+/mo budgets.
September 11, 2025
Published: September 9, 2025|Updated: September 11, 2025
4 mins
Discover the fundamental differences between traditional SEO and Answer Engine Optimization (AEO). Learn why your SEO strategy might not be enough for AI search visibility and how to adapt for the new era of AI-powered discovery.
AI search has fundamentally changed how B2B buyers discover products and services. Traditional SEO strategies that have worked for the past decade are no longer sufficient if you want to be recommended in AI-powered answers.
50% projected drop in traditional search by 2028 as users shift to AI assistants
3-4x higher conversion rates for visitors coming via AI search compared to traditional organic traffic
In a recent study, Ahrefs found that while AI-referred traffic accounted for only 0.5% of their website traffic, it generated 12% of their total signups - a 23x higher conversion rate than traditional traffic.
Key Insight If you haven't adapted your search strategy for AI, your company could be invisible to a rapidly growing segment of the market - even if you've been doing traditional SEO for years.
Traditional search vs AI search: a fundamental shift #
AI search represents a completely different paradigm:
Users have conversations with AI assistants
They provide extensive context and constraints
The AI conducts web searches behind the scenes
It synthesizes information from multiple sources
Returns a personalized answer based on the user's unique situation
This shift from short queries to conversations and from random blue links to personalized answers changes everything about how we need to approach search optimization.
Unlike traditional search engines that take your query verbatim, AI models transform user prompts into dozens of sub-queries through a process called "query fan-out." These models:
Create multiple search variations with filters and operators
Search for specific facts across different phrasings
Pull relevant snippets from multiple sources
Merge information into one cohesive answer
This is fundamentally different from traditional SEO where you optimize for specific keywords. With AI search, you need to ensure your information is discoverable across many different phrasings and angles.
In traditional SEO, we chase stable page positions - trying to rank number one for specific keywords. But in AI search:
There's no single "position one" to hold
Rankings change based on user context and constraints
Two users with similar queries but different budgets or company sizes get completely different recommendations
Memory and conversation history influence results
This means smaller companies with lower domain authority can become the recommended solution if they optimize correctly for AI search - something impossible in traditional SEO where incumbents dominate.
Traditional SEO relies heavily on backlinks as the primary authority signal. AI search looks for something different:
Corroboration across multiple sources: Review platforms, directories, press, documentation, communities, Wikipedia
Consistency of facts: If multiple third parties say one thing about your pricing but your website says another, AI trusts the consensus
Natural language mentions: Authentic discussions in forums and communities carry significant weight
Think of it this way Your website is like your resume where you say good things about yourself. In AI search, the models are calling your references to verify your claims. What others say about you matters more than what you say about yourself.
The three surface areas of modern search strategy #
A winning search strategy in 2025 and beyond must consider three primary surface areas:
Being discoverable via web search by humans searching keywords in traditional search engines. This remains important but is no longer sufficient on its own.
Getting your most important facts baked into the actual AI models themselves so future versions know about your company without needing web search. This provides long-term defensibility.
We're still in the first innings of AI search. While trillion-dollar companies battle for dominance, the playbook is still being written. Most companies haven't adjusted their strategies yet, creating a massive opportunity for early movers.
The companies that adapt now - that understand the fundamental differences between SEO and AEO - will secure lasting advantages in how AI systems understand and recommend their products.
