For more than 20 years, businesses have worked to improve their visibility on Google through Search Engine Optimization, or SEO.
SEO is still critically important. But the way people search for information is changing.
Instead of simply typing a few words into Google and choosing from a list of websites, consumers are increasingly asking conversational questions of ChatGPT, Google AI Mode, Google AI Overviews, Gemini and other AI-powered search tools.
That change has created a related discipline: Generative Engine Optimization, commonly called GEO.
The simplest way to understand the difference between SEO and GEO is to think about the difference between using a library card catalog and asking a knowledgeable friend for a book recommendation.
SEO helps your business get found in search results. GEO helps your business get understood, cited and recommended in AI-generated answers.
They overlap significantly, but they are not identical.
| Traditional SEO | AI GEO |
|---|---|
| Optimizes for search engine results | Optimizes for AI-generated answers |
| Goal is often ranking a webpage | Goal is often being cited or recommended |
| Commonly measured through rankings, clicks and traffic | Commonly measured through mentions, citations and recommendation position |
| Keywords remain important | Topics, entities, context and relationships become increasingly important |
| Google rankings are a major focus | Visibility across multiple AI platforms matters |
| Your webpage is usually the destination | AI may summarize your information before a user visits your site |
Importantly, GEO does not replace SEO.
Google itself has emphasized that traditional SEO best practices remain foundational to visibility within its generative AI search experiences.
A strong AI search strategy therefore isn’t SEO or GEO.
It is SEO plus GEO.
Imagine walking into a huge library looking for a book about starting a vegetable garden in Eastern Washington.
In the traditional library model, you might use the card catalog.
You search terms such as:
Vegetable gardening
Washington gardening
Raised-bed gardening
Dry-climate gardening
The catalog examines how books have been categorized and tells you which books appear relevant.
You receive a list.
You then decide which book you want.
Traditional search engines work in a somewhat similar way.
You might search Google for:
“best landscaping company Spokane”
Google evaluates potentially relevant webpages using hundreds of signals and returns search results it believes will best satisfy your query.
A traditional SEO strategy attempts to make your company one of those highly visible results.
That can involve:
Technical website optimization
Keyword research
On-page optimization
Helpful content
Internal linking
Local SEO
Google Business Profile optimization
Backlinks and authority building
Structured data
Website performance
Reviews and reputation signals
SEO helps the search engine find, understand and rank your pages.
But AI search changes the experience.
Now imagine that instead of using the library catalog, you ask a friend:
“I’m a beginner gardener in Spokane. I have a fairly small backyard, don’t want to spend a fortune, and I’d really like a book that explains raised beds and what actually grows well in our climate. What would you recommend?”
That’s a very different request.
Your friend doesn’t simply give you every book containing the words gardening and Spokane.
Your friend interprets what you mean.
They may consider:
Your location
Your experience level
Your specific problem
Which books are considered authoritative
Which books contain the information you need
What other gardeners recommend
Which authors have credible experience
Which book is the best fit for your situation
Then your friend might answer:
“I’d start with these three books. Here’s why.”
That interaction is much closer to the experience consumers have with AI search.
Someone might ask:
“Who would you recommend for a landscaping project in Spokane if I need both a retaining wall and a paver patio?”
Or:
“Which Spokane window-covering companies specialize in motorized shades and have strong customer reviews?”
The AI system doesn’t necessarily return ten blue links.
Instead, it may form an answer and recommend several businesses.
That distinction is enormously important.
In traditional SEO, a major objective might be:
Rank in the top three Google results for an important search.
In AI GEO, the objective may become:
Be one of the three companies the AI recommends when someone asks an important buying question.
Those are related goals, but they are not necessarily the same.
A company may rank reasonably well in Google yet appear infrequently in AI recommendations.
Another company may have a strong reputation across trusted third-party websites and repeatedly appear in AI answers even when its own website doesn’t rank #1 for every related keyword.
Why?
Because AI systems may assemble answers using information about a company from multiple places across the web.
That can include:
The company’s website
Google Business Profile information
Reviews
Industry directories
Local publications
Professional organizations
Manufacturer websites
News articles
Comparison articles
Forums and community discussions
Videos
Other trusted third-party sources
This introduces an important GEO concept:
Traditional SEO has always included off-site authority.
But AI search makes a company’s broader digital footprint even harder to ignore.
An AI system may be trying to answer questions such as:
Who is this company?
Where does it operate?
What does it specialize in?
Is the company credible?
What evidence supports its claims?
What do independent sources say about it?
Is information about the company consistent?
Is this company relevant to this particular question?
Your website provides part of that evidence.
The rest of the internet may provide another part.
One helpful way to think about the evolution is this:
Traditional SEO often focuses heavily on webpages. GEO places additional emphasis on the business or organization represented by those pages.
In search terminology, that business is an entity.
Suppose a contractor’s website says:
“We are Spokane’s premier outdoor living experts.”
That is a claim.
But suppose Google, AI systems and consumers can also find:
Detailed project examples
Named employees and their experience
Photographs of completed work
Customer reviews
Manufacturer certifications
Local news coverage
Industry memberships
Helpful articles demonstrating expertise
Consistent business information across trusted websites
Now there is evidence supporting the entity.
GEO isn’t simply about repeating a keyword more frequently.
It is about making it easier for machines—and people—to understand who you are, what you’re qualified to do and why you deserve to be recommended.
AI search increasingly involves specific conversational questions.
That means a page shouldn’t merely contain information somewhere within 2,000 words of copy.
Important answers should be easy to identify and extract.
Strong AI-friendly content often uses:
Clear H2 and H3 headings
Questions as headings when appropriate
Concise answer paragraphs
Bulleted lists
Comparison tables
Definitions
Original statistics
Examples
First-hand experience
Specific recommendations
Supporting evidence
Clearly identified authors and businesses
For example, instead of burying an answer to:
“How deep should the base of a paver patio be?”
inside a long article, a contractor might provide a clear section:
Followed immediately by a direct answer, supporting explanation, installation variables and possibly a table.
That structure helps people.
It also gives search and AI systems clearer information to interpret.
One of the biggest changes involves measurement.
Traditional SEO reporting commonly includes:
Keyword rankings
Organic traffic
Search impressions
Click-through rates
Leads
Conversions
Google Business Profile activity
Backlinks
Those metrics remain valuable.
But AI search requires additional measurements.
A business may also need to track:
Percentage of relevant AI queries where the company appears
Percentage of queries where the company appears in the top three recommendations
Average recommendation position
AI platforms where the business appears
Competitors most frequently recommended
Sources AI systems cite
Topics where competitors outperform the company
Changes in recommendation visibility over time
This is one reason simply adding “AI” to an existing SEO report isn’t enough.
You cannot meaningfully improve AI visibility if you’re not measuring AI visibility.
Businesses should resist the temptation to view SEO and GEO as competing strategies.
In reality, they reinforce one another.
| SEO Activity | SEO Benefit | Potential GEO Benefit |
|---|---|---|
| Improve crawlability | Search engines can access pages | AI/search systems can more easily discover information |
| Create authoritative content | Improves relevance and ranking potential | Gives AI systems useful source material |
| Add structured data | Helps machines understand page information | Improves machine-readable entity/context signals |
| Build quality backlinks | Strengthens authority | Expands third-party validation |
| Earn local mentions | Supports local SEO | Provides independent evidence about the business |
| Publish expert content | Targets informational searches | Creates quotable, answer-ready material |
| Improve reviews/reputation | Supports local conversion and visibility | Strengthens independent reputation signals |
| Improve entity consistency | Strengthens local/search understanding | Helps establish who the business is |
That’s why a modern search strategy should not abandon SEO.
It should expand SEO to account for the way AI systems discover, interpret, synthesize and recommend information.
Imagine two HVAC companies.
Company A has:
A technically solid website
Good local keyword rankings
Optimized service pages
Reasonable backlinks
It performs well in traditional Google Search.
Company B has all of those things, plus:
Detailed answers to common homeowner questions
Original installation examples
Strong Organization and service-related structured data
Consistent business information
Numerous independent local mentions
Manufacturer references
Strong review visibility
Helpful comparison content
Demonstrated expert authorship
Content frequently supporting the questions people ask AI systems
Company B has created more than a search-optimized website.
It has created a machine-understandable body of evidence about the company and its expertise.
That is where SEO begins moving into GEO.
If prospective customers are using AI systems to research companies, compare options or ask for recommendations, the answer is increasingly yes.
That doesn’t mean abandoning everything your business has done for SEO.
Quite the opposite.
Good SEO provides the foundation.
GEO builds upon that foundation by asking additional questions:
Can AI systems access our information?
Do they understand our company correctly?
Do they understand what we specialize in?
Is our content structured around the questions customers actually ask?
Do we provide evidence supporting our expertise?
Are authoritative third parties talking about us?
Are we appearing when AI systems make recommendations?
Which competitors are being recommended instead?
Why?
Those are becoming fundamental marketing questions.
For years, the objective of search marketing could largely be summarized in two words:
Be found.
AI search adds another objective:
Be recommended.
Traditional SEO helps put your book into the library catalog where people can find it.
AI GEO helps make your business the book a knowledgeable friend pulls off the shelf and says:
“This is the one I’d recommend.”
The businesses that understand that distinction early will have an important advantage as search continues evolving.
No. GEO builds upon many of the same technical, content and authority foundations used in SEO. Google has specifically stated that SEO best practices continue to matter for its generative AI search experiences.
GEO stands for Generative Engine Optimization. The term describes efforts to improve the visibility of information, brands and websites within answers produced by generative search and AI systems.
Yes. Traditional rankings and AI recommendations measure different forms of visibility. A company may have strong organic rankings but lack the entity signals, third-party authority, content structure or supporting evidence that contributes to visibility for certain AI-generated answers.
Useful measurements can include AI recommendation frequency, top-three recommendation share, average recommendation position, competitor visibility, citations and the sources used to support AI answers.
Most established businesses should optimize for both. SEO remains the foundation for web search visibility, while GEO expands the strategy to address AI-generated search, citations and recommendations.
As founder of The Marketing Crew, Jason Yates helps small, independent businesses craft their message and image to better compete in a rapidly changing economic and demographic environment. With over 25 years of professional marketing experience, Jason and The Marketing Crew are available to help you re-shape your brand, or act as your marketing team – guiding and implementing your marketing strategies.
Jason can be reached at (509) 795-0983 or jason@marketingcrew.org.
