I recently saw someone claim on LinkedIn that GEO (Generative Engine Optimization) equals SEO (Search Engine Optimization).
They were not trying to provoke a reaction, but rather, they had noticed something that looked reasonable on the surface.
When they tested ChatGPT for local recommendations, many of the same companies appeared that Google already shows in local results. From that observation, they drew a straight line and assumed GEO and SEO are the same because (allegedly) ChatGPT crawls Google. If the outputs overlap, then the systems must work the same way.
That conclusion feels tidy, but it skips the part that actually matters.
The overlap does not exist because AI systems reward traditional SEO tactics. It exists because local SEO establishes something that AI systems need far more than rankings.
The short version is this: local SEO transfers to AEO (Answer Engine Optimization) and GEO not because AI systems work like search engines, but because local SEO establishes clear, verified business entities that answer engines and LLMs can confidently reference without guessing.
Once you separate ranking mechanics from entity recognition, the behavior of AI systems becomes much easier to explain.
What Actually Changed When AI Entered the Picture
Traditional SEO focused on ranking content and pages.
AI systems are focused on referencing entities.
That shift sounds subtle, but it changes how visibility works. Search engines evaluated whether a page deserved to rank higher than another page. AI systems evaluate whether a business deserves to be named at all.
That decision carries risk. If an AI system recommends the wrong business, the failure feels personal to the user, not abstract like a poor ranking.
Because of that risk, AI systems default toward confidence and caution.
They prefer entities that feel stable, verifiable, and easy to understand.
Why Most SEO Tactics Have No Impact on AEO and GEO
Many SEO techniques were designed to influence comparative ranking, and not to establish a real-world identity.
Examples include:
- Targeting keywords and content relevance
- Acquiring links tactically, rather than for boosting an entity like author or business
- Optimizing tactical on-page items like meta tags, image alt-tags, etc. for weaving in keywords
- Expanding content expansion without any thought to reinforcing the entity itself
These tactics can help one web page outrank another page. They do very little to help an AI system decide whether a business is important enough to recommend.
AI systems need verification signals, not persuasion signals.
That is where most SEO strategies simply won’t work on AI platforms. So no, SEO does not equal AEO nor GEO.
Why Local SEO Is Fundamentally Different
Local SEO was never just about rankings, even though rankings were the visible outcome.
At its core, local SEO exists to resolve ambiguity.
Machines need to understand:
- Whether a business is real
- Where it operates
- What category it belongs to
- Whether others can confirm its legitimacy and reputation
Local SEO addresses these questions directly. It forces businesses to define themselves clearly, consistently, and verifiably across the web.
As it turns out, that clarity is highly transferable to AI systems.
The Entity Signals Local SEO Creates
When local SEO is done the right way, it produces a set of signals that machines trust.
These signals include:
- Structured data that defines the business entity
- Verified business profiles that confirm legitimacy
- Consistent name, address, and phone information
- Reviews tied to a specific identity and location
- Clear categorical and service definitions
All of these signals depend on alignment, as opposed to traffic or rankings.
Alignment reduces uncertainty, which in turn influences whether or not AI systems will include your business.
How Local SEO Transfers to Answer Engines (AEO)
Answer engines rely on retrieval. They pull information from live sources and assemble responses from extractable facts.
To include a business, an answer engine needs confidence that:
- The entity is clearly defined
- The attributes remain stable
- Conflicting data is minimal
- The risk of hallucination is low
Local SEO supports all of these requirements. When your business has consistent entity signals, answer engines will find it to extract. However, if your business has fragmented or contradictory data, answer engines are likely to see it as risky to recommend.
And that risk will mean you aren’t included at all when people ask for recommendations.
This explains why some businesses appear in AI-generated answers even when their traditional organic rankings are unremarkable.
The system isn’t rewarding SEO performance…it’s responding to entity clarity.
Why Content Alone Can’t Replace Entity Signals
High-quality content still matters, but you shouldn’t expect it to replace entity foundations.
- Content explains ideas
- Entity signals establish reality
An answer engine may trust a paragraph, but it will hesitate to name your business unless it exists clearly in the answer engine’s reference framework. Without strong entity signals, even excellent content will struggle to earn inclusion.
Local SEO anchors content to a defined, verifiable entity, which makes extraction possible.
How Local SEO Transfers to LLMs (GEO)
Large language models operate differently from answer engines, but the dependency on entity clarity remains.
LLMs rely on learned patterns rather than live retrieval. Those patterns form through repeated exposure to consistent information over time.
Local SEO creates that repetition naturally.
- Every directory listing reinforces the same entity attributes
- Reviews confirm relevance tied to identity
- Each verified profile reduces contradiction
Over time, the model will become familiar with your business as an entity, which will boost its confidence in your business itself. And that is how you can maximize the likelihood that LLMs will mention you.
You don’t have to directly optimize for GEO. It will simply work because your business maintains a coherent identity across the web.
Why Large Brands Often Struggle With AI Visibility
Scale doesn’t guarantee clarity.
Large organizations often fragment their entity signals across regions, platforms, and internal teams.
Perhaps they use inconsistent naming conventions, continue to list old addresses, or fail to successfully shift categories when the time to do so arises.
From a human perspective, these issues seem minor. But for LLMs, they introduce doubt.
Local businesses that maintain clean, consistent entity signals often outperform much larger competitors in AI recommendations, because they are easier to understand and verify.
It’s all about how clear you are establishing and managing your entity. This is much more important that how big you are.
How AEO, GEO, and SEO Differ in Practice
Even if there is some overlap between the various systems with regard to local SEO, they are not interchangeable.
Each type of “engine” will evaluate your credibility in a unique way.
| Dimension | Traditional SEO | AEO | GEO |
| Primary focus | Ranking pages | Extracting answers | Synthesizing knowledge |
| Core unit | URL | Entity and attributes | Entity and learned patterns |
| Main risk | Irrelevance | Hallucination | Misrepresentation |
| Role of local SEO | Indirect | High confidence inputs | Repeated entity reinforcement |
Local SEO transfers because it aligns with the needs of AEO and GEO, not because those disciplines are identical to or a new version of SEO.
The Risk of Skipping the Foundation
Many businesses chase AI visibility through tools, prompts, and content experiments without addressing entity clarity.
They try to influence outputs before establishing identity.
If you apply old school SEO techniques and measurement systems to AEO or GEO, the results will be inconsistent, confusing, and misleading.
Focus on the entity. That’s how to get LLMs and answer engines to care about you and your business entity.
Fortunately for all of us, local SEO is an ideal strategy for removing ambiguity at the source. If you serve a local market and want to show up on AI systems, you need to take local SEO seriously. Bottom line.
How to Think About Local SEO Now
I recommend we all stop viewing local SEO as a channel. It now functions as entity infrastructure.
That infrastructure supports:
- Search visibility
- Answer inclusion
- Generative recognition
Each layer builds on the same truth. The business exists, operates in a defined context, and can be verified by others.
AI systems will reward that certainty.
The Takeaway
The businesses that appear consistently across Google, ChatGPT, and other AI systems are not winning because they discovered a new tactic.
They appear because AI systems feel safe referencing them.
Local SEO creates that safety by establishing entity clarity, not by manipulating rankings.
That is why it transfers, while most SEO tactics don’t.
And it’s also why we can’t reduce GEO to a rebrand of SEO. That naïve mindset will misunderstand the deeper shift that is already happening right before our eyes.
Tommy Landry
Latest posts by Tommy Landry (see all)
- Why Local SEO Transfers to AI When Most SEO Tactics Don’t - February 10, 2026
- The Great Decoupling of Search - January 13, 2026
- How to Use AI to Accelerate Content Creation Without Losing Authenticity - January 6, 2026
