# GEO vs AEO vs LLMO vs SGE: An Honest Taxonomy > Four acronyms, mostly the same thing — and a few clear distinctions worth keeping. We pulled the original definitions, checked who uses which term, and argue which one should win. Canonical: https://geosalience.com/foundations/geo-vs-aeo-vs-llmo-vs-sge Published: 2026-05-31T00:00:00.000Z Updated: 2026-06-08T00:00:00.000Z Pillar: foundations Authors: geosalience --- Four acronyms are in active use: **GEO**, **AEO**, **LLMO**, **SGE**. The trade press uses them interchangeably; academic literature draws sharper distinctions. Here's where each came from, what they actually mean, and which one we use on this site (and why). ## TL;DR - **GEO** — Generative Engine Optimization. Aggarwal et al. (2024). Specific to LLM-generated answers. - **AEO** — Answer Engine Optimization. Predates LLMs by ~10 years. Broader umbrella including voice assistants and featured snippets. - **LLMO** — Large Language Model Optimization. Effectively a synonym for GEO with a slight emphasis on no-browsing scenarios. - **SGE / AI Overviews** — Google's specific product, not a discipline. We use **GEO** on this site. Reasoning at the end. ## GEO: Generative Engine Optimization **Coined:** [Aggarwal, Saxena, et al. (2024)](https://arxiv.org/abs/2311.09735) in the paper "GEO: Generative Engine Optimization", which proposed the term and tested 9 optimisation strategies against ChatGPT, BingChat, and Perplexity. **Defined as:** "Optimisation of content for generative engines — search-like systems that respond with a generated answer rather than a list of links." **Scope:** Specifically generative. The engine doesn't retrieve a pre-existing answer; it synthesises one from retrieved sources. **Adoption:** As of mid-2026, "GEO" is the most-cited term in academic literature and is being adopted in the trade press (SEMrush, Ahrefs, MarTech blogs). ## AEO: Answer Engine Optimization **Coined:** ~2014–2015, in the SEO trade press, in the context of optimising for featured snippets ("position zero") and voice assistants (Alexa, Siri, Google Assistant). **Defined as:** Structuring content so that an "answer engine" — a system that responds to a query with a direct answer rather than a SERP — uses your content as the answer. **Scope:** Pre-LLM. Includes featured snippets, knowledge-graph cards, voice-assistant responses, and now AI Overviews. **Adoption:** Still in use, often as a synonym for GEO. Older SEO professionals tend to prefer it. ## LLMO: Large Language Model Optimization **Coined:** Variously, around 2023, in the marketer-Twitter / LinkedIn ecosystem. No canonical academic paper. **Defined as:** Optimisation of content for citation behaviour by LLMs, irrespective of whether the LLM is wrapped in a search interface. **Scope:** Slightly broader than GEO — includes the no-browsing case (an LLM answering from [training data alone](/foundations/knowledge-cutoff-and-web-access), bounded by its knowledge cutoff). **Adoption:** Less common than GEO in academic literature; more common in B2B marketing copy. ## SGE / AI Overviews **Coined:** Google, [May 2023 announcement](https://blog.google/products/search/generative-ai-search/), originally as Search Generative Experience (SGE). Rebranded to AI Overviews in May 2024. **Defined as:** A specific Google product feature — the generative AI panel that appears above traditional search results. **Scope:** Not a discipline; not a category of optimisation. A specific surface on a specific engine. **Use:** Only when discussing Google specifically. Saying "I do SGE" is like saying "I do Featured Snippets" — a sub-discipline, not the umbrella. ## Where they overlap | Concept | GEO | AEO | LLMO | SGE | |---|---|---|---|---| | LLM-generated answer? | Yes | Sometimes | Yes | Yes | | Pre-LLM scope? | No | Yes | No | No | | Includes no-browsing LLM behaviour? | Edge | No | Yes | No | | Google-specific? | No | No | No | Yes | ## Why we use GEO Three reasons: 1. **Specificity.** GEO names the generative mechanism, which is the actual thing that changed. AEO and LLMO are either older or vaguer. 2. **Academic anchor.** Aggarwal et al. (2024) gives us a paper to point to. Trade-press terms drift; cited academic terms are more durable. 3. **Trade trajectory.** Google Trends and academic indexing both show GEO overtaking AEO in 2025–2026. This is a judgment call. If you prefer AEO, the practical advice is the same. ## FAQ **What's the difference between GEO and AEO?** GEO (Generative Engine Optimization), coined by Aggarwal et al. in 2024, is specific to LLM-generated answers — the engine synthesises an answer from retrieved sources rather than returning a list of links. AEO (Answer Engine Optimization) predates LLMs by about ten years; it is the broader umbrella that also covers featured snippets ("position zero") and voice assistants. Older SEO professionals tend to prefer AEO, often as a synonym for GEO. **Is LLMO the same thing as GEO?** Effectively yes. LLMO (Large Language Model Optimization) is a near-synonym for GEO, with a slight emphasis on the no-browsing case — an LLM answering from its [training data alone](/foundations/knowledge-cutoff-and-web-access), bounded by its knowledge cutoff. It has no canonical academic paper and is more common in B2B marketing copy than in the literature. **Is SGE a type of optimization?** No. SGE (Search Generative Experience), rebranded to AI Overviews in May 2024, is a specific Google product feature — the generative panel above the search results — not a discipline. Use the term only when you mean Google specifically; saying "I do SGE" is like saying "I do featured snippets." **Which term should I use?** We use GEO, for three reasons: it names the generative mechanism that actually changed; it has an academic anchor (Aggarwal et al., 2024) that drifting trade-press terms lack; and both Google Trends and academic indexing show GEO overtaking AEO across 2025–2026. It is a judgment call — if you prefer AEO, the practical advice is the same. ## See also - [What is Generative Engine Optimization (GEO)?](/foundations/what-is-geo) — the longer primer. - More in the [Foundations](/foundations) pillar — the theory and mechanics of AI search. - [llms.txt: spec, 100-domain adoption audit, and setup](/technical/llms-txt-spec-adoption-setup) — a concrete, audited technical method once you have settled on the terminology. - [Glossary: GEO](/glossary/geo), [AEO](/glossary/aeo), [LLMO](/glossary/llmo), [SGE](/glossary/sge).