AEO vs LLMO Differences — The 70% Overlap, the 30% Unique, and Where GEO Sits

At SEO industry conferences in 2026, AEO, LLMO, and GEO show up in the same session as three parallel terms. Speakers disagree on what they mean, and the audience is confused. Neil Patel says "these are all part of SEO," Profound says "AEO and GEO are the same thing," and emarketer writes "the overlap is 80%." Nothing is settled.

Conclusion up front. The containment is AEO ⊂ GEO ⊃ LLMO — AEO and LLMO are "sibling concepts that overlap but target different platforms." AEO targets "answer-returning search systems" (Google AI Overview / ChatGPT Search / Perplexity); LLMO targets "LLM chat in general" (including non-search use of ChatGPT, Claude, Gemini). The shared techniques are 70%; the unique ones are 30% — that's my reading of where things sit as of May 2026.

My stance up front. Getting too caught up in the fine-grained terminology distinctions makes you miss the point. AEO, LLMO, and GEO all fundamentally aim at the same thing: "get cited, referenced, and surfaced correctly by AI, even when humans don't read you." Implement the shared 70% and all three improve. This article covers the precise definitions, the core shared techniques, the unique parts, an industry-by-industry priority matrix, and the pitfalls — as of May 2026. As prerequisite reading, see What is AEO and What is LLMO.

1. AEO, LLMO, GEO — Three New Terms Trending at Once

From late 2024 into 2026, the SEO industry has produced three new acronyms at once: AEO (Answer Engine Optimization), LLMO (Large Language Model Optimization), and GEO (Generative Engine Optimization). The usage drifts slightly between commentators, and audiences are confused.

Concrete examples: Neil Patel sorts AEO, GEO, and LLMO all as "part of SEO," Profound argues "AEO and GEO are the same," and emarketer writes "the GEO/AEO overlap is roughly 80%." Stackmatix uses the containment "AEO ⊂ GEO," and Jasper positions "LLMO as a technical subset of GEO."

The debate over which is "correct" isn't especially productive. All three terms were born recently, and there's no settled industry standard. What matters is being explicit about "for what purpose, against which platform, what we're optimizing." This article proposes the most pragmatic ordering as of May 2026: AEO ⊂ GEO ⊃ LLMO, with AEO and LLMO as siblings that target different platforms.

2. The Definitions — Sorted in Three Lines

The difference in one sentence: AEO is "be chosen as the answer when a user searches," LLMO is "be recalled when a user asks an AI directly," GEO is "the umbrella that covers both." The boundaries are fuzzy, and the same techniques apply across all three in many scenarios — but "the platform being optimized for" and "what success looks like" differ.

3. Comparison Table — Target, Goal, Metrics

The differences look sharp on paper, but the actual playbook overlaps heavily. The next section sorts out the "shared 70%."

4. The 70% Overlap — Shared Techniques That Work for Both

These seven are the core techniques that work for both AEO and LLMO. Implement them and you cover 70% of AEO + 70% of LLMO at the same time. It's the highest-leverage zone in the field.

Personally, my framing is "just implementing these seven raises your win rate for both AEO and LLMO." These aren't new tactics — they're "the main road of content quality." AI ultimately rewards "content that's good for humans." E-E-A-T, structure, first-party data, clear conclusions — the things SEO has recommended for years now work for AI too.

5. The 30% That Diverges — Each Side's Own Strategy

With the shared 70% in place, the remaining 30% of unique work is where differentiation happens.

The most important distinction in the unique zone: AEO is "tricks for the SERP," LLMO is "embedding into the corpus." AEO has a lot of technical optimization that tracks Google spec changes; LLMO is closer to long-term brand building. Get an article on Wikipedia, build a reputation on Reddit, ship an open-source project on GitHub — these are six-month to multi-year investments, but once you're in the training corpus, you compound for years.

6. Where GEO Sits — The Parent Concept of AEO and LLMO

GEO (Generative Engine Optimization) is most often used as the parent concept containing AEO and LLMO. emarketer, Stackmatix, and Jasper all order it this way.

In practice, saying "we do GEO" implicitly covers both AEO and LLMO. So in many cases, "we do GEO" internally or to outside audiences causes the least confusion. AEO and LLMO are terms for going deep on individual techniques; GEO is the term to use at the strategy layer — that's the comfortable settlement.

7. Which to Prioritize — A Matrix by Industry

When resources are tight, which should you invest in first — AEO or LLMO? Below is a judgment grid by industry and business model.

As a rule, B2C with clear search intent → AEO; B2B and "advise / recommend" demand-heavy industries → LLMO. But to repeat the point, if you implement the shared 70% first, you build the foundation for both at the same time, so there's no reason to give anything up over industry. The prioritization conversation is really about "which way to direct the final 30%."

8. Three Pitfalls You Must Avoid

Pitfall ①: Over-fixating on terminology differences

Burning hours on "is AEO or LLMO the right answer? what about GEO?" — spend too much time in terminology debates and you miss the substance. All three are new terms with fluid definitions. The core that's "good content for humans and for AIs" is shared across all three. Far better ROI to spend the time on implementing the shared 70% than on naming arguments.

Pitfall ②: Downplaying SEO

Neither AEO nor LLMO works without an SEO foundation. AI Overview and Featured Snippet cite from top-ranked pages, ChatGPT Search goes through Bing search results, Perplexity is similar. "SEO is old, AEO/LLMO is new" is a false dichotomy. Order it as a three-layer stack: SEO (rank) + AEO (cite-friendly design) + LLMO (recall-friendly design).

Pitfall ③: Being vague about measurement

AEO needs Snippet appearance rate and AI Overview citation; LLMO needs brand recall rate and recommendation rate inside AI prompts — different from SEO (rank, traffic). Watch only the old SEO metrics and you end up saying "we're doing AEO/LLMO but we don't see results," and the program gets killed. Just recording "ask ChatGPT monthly 'what do you recommend in X area' and note where our brand ranks" is enough for a useful qualitative benchmark.

Summary

The terminology is sprawling, but the substance is simple: "make content that's good for humans and AIs, structure it, attribute it, feed it to the AI." That's the common ground of AEO, LLMO, and GEO. Implementing the shared 70% techniques first is the shortest path — much better than memorizing terms. The industry-priority conversation is about the last 30%; most organizations should put their time into "the shared 70% first." SEO is the foundation, AEO and LLMO are the two layers above, GEO is the umbrella name for them — keep this three-layer structure in your head and the terminology noise stops mattering.

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