SEO, AEO, GEO, LLMO, AIO, AI SEO — if the acronyms around AI search leave you unsure whether you need one strategy or five, you are not alone. Agencies and tool vendors have strong incentives to present each label as a separate discipline with its own budget. Meanwhile, the people running search programmes mostly want to know which tasks are actually new and which are the same work with a new name.
This article untangles the terminology, shows where the tactics overlap and where they genuinely diverge, and recommends a way to organise the work so you don't duplicate effort or pay twice for the same thing.
Short version: treat AEO and GEO as extensions of SEO focused on answers and AI-generated responses. Most of the work is shared. A smaller set of tasks — prompt tracking, cited-source analysis, brand-fact accuracy across AI tools — is genuinely new and deserves explicit ownership.
Key Takeaways
- SEO, AEO and GEO share the same foundations: crawlable, indexable, helpful content and a trustworthy brand.
- Google explicitly says optimising for its generative AI features is “still SEO”.
- The genuinely different parts are measurement (prompts, mentions, citations), off-site brand mentions and answer accuracy across multiple AI platforms.
- Organise one programme with one prompt and keyword set, not separate SEO, AEO and GEO teams.
- Be sceptical of tactics sold as AI-only, such as special files or content chopped into fragments.
What each term means
| Term | Stands for | Focus | Where it came from |
|---|---|---|---|
| SEO | Search engine optimisation | Visibility in search engines: crawling, indexing, ranking, clicks | Established discipline since the 1990s |
| AEO | Answer engine optimisation | Being the direct answer: snippets, voice and AI answers | Industry term; usage varies widely |
| GEO | Generative engine optimisation | Visibility and citation inside AI-generated responses | Named in a 2023 research paper (KDD 2024) |
| LLMO / AI SEO | Large language model optimisation | Usually used as a synonym for GEO | Industry term |
The term GEO was popularised by a research paper from Aggarwal and colleagues, published at the KDD 2024 conference (arXiv). It proposed a framework and benchmark for improving content visibility in generative engine responses and reported that its methods could boost visibility by up to 40% in its test setting, with effectiveness varying by domain. Those are lab results on a benchmark, not a guarantee for live products.
“Generative Engine Optimization (GEO), the first novel paradigm to aid content creators”
— Aggarwal et al., GEO: Generative Engine Optimization
For a fuller list of definitions, see our AI search glossary, and for a deep dive into GEO tactics, our existing guide to generative engine optimization.
Google's view: it's still SEO
Google's guide to optimizing for generative AI features (updated July 2026) names AEO and GEO directly and says that from Google's perspective they are part of SEO:
“optimizing for generative AI search is optimizing for the search experience, and thus still SEO.”
— Google Search Central, Guide to optimizing for generative AI features
The same guide says you don't need AI-specific files, Markdown or markup, that there's no requirement to break content into tiny pieces, and that seeking inauthentic mentions isn't as helpful as it might seem. That's Google's position for Google's AI features; other platforms such as ChatGPT, Perplexity and Claude run their own retrieval systems and publish less guidance, which is one reason multi-platform measurement matters.
Where the tactics overlap and where they diverge
| Activity | SEO | AEO | GEO | Shared or distinct? |
|---|---|---|---|---|
| Crawlability and indexing | ✔ | ✔ | ✔ | Shared (plus AI crawler access checks) |
| Search intent and topic research | ✔ | ✔ | ✔ | Shared; GEO adds conversational prompts |
| Helpful, original content | ✔ | ✔ | ✔ | Shared |
| Answer-first structure | Helpful | Core | Core | Mostly shared |
| Structured data | ✔ | ✔ | ✔ | Shared; not an AI-only requirement |
| Backlinks | Core | Supportive | Supportive | Shared |
| Unlinked brand mentions and reviews | Supportive | Supportive | Core | Leans GEO |
| Rank tracking | Core | Snippet tracking | Prompt and citation tracking | Distinct measurement |
| Brand-fact accuracy across AI tools | Rarely | Sometimes | Core | Distinct |
Semrush's comparison of traditional and AI SEO draws similar lines: the technical foundations are common, while AI SEO adds longer conversational prompts, passages that make sense out of context, mentions without links and new metrics such as share of voice and sentiment. Industry practice reflects the overlap: in Semrush's June 2026 survey, 77% of marketers placed AI search within SEO.
How to organise the work without duplication
- One programme, one owner. Put AI search inside the SEO programme with a named owner; see building an AI search process.
- One research set. Combine keywords and prompts into one list grouped by topic and search intent.
- One content brief template that covers ranking needs and answer needs together: a direct answer, specifics, evidence and author expertise. See answer-first writing.
- One technical checklist that includes Googlebot, Bingbot and the AI search crawlers.
- Add the distinct pieces explicitly: prompt and citation tracking, cited-source analysis, and a process for fixing wrong brand facts.
- One report that shows rankings, organic traffic, AI mentions, citations and AI referrals side by side.
A worked example
Imagine a regional accounting firm that wants more enquiries. A split approach would hire one provider to “do SEO” (service pages, local listings, links) and another to “do GEO” (rewrite pages for AI, track ChatGPT answers). Both would audit the same site, brief the same writers and report different numbers.
An integrated approach starts with one list: “accountant for small business in Leeds” alongside prompts like “Which Leeds accountants specialise in sole traders and offer fixed fees?” One brief updates the small-business service page so it answers that question directly, names the fee approach and shows the qualified accountants behind it. The same Business Profile clean-up serves Maps rankings and AI answers. PR work targets the local business publications that AI tools cite. One monthly report shows rankings, enquiries, AI mentions and citations together.
The second approach costs less, moves faster and avoids conflicting advice — and nothing in it ignores AI search.
When separate specialists make sense
Large organisations sometimes do benefit from a specialist focused on AI visibility — for example, to run multi-platform prompt tracking across many markets or to coordinate PR around the sources AI cites. The key is that the specialist works inside the search programme, sharing research, briefs and reporting, rather than running a parallel strategy.
Common mistakes
- Buying separate SEO, AEO and GEO retainers that cover the same content and technical work.
- Rewriting good pages “for AI” into fragmented, keyword-stuffed Q&A blocks.
- Relying on AI-only gimmicks such as special files that Google says it doesn't need.
- Ignoring off-site signals because they don't fit a traditional SEO scope.
- Arguing about labels instead of agreeing tasks, owners and metrics. Our post on AI search myths covers more misconceptions.
Conclusion
You don't need three strategies. You need one search strategy that covers rankings, answers and AI-generated responses, with explicit ownership of the few things that are genuinely new. Read more on why the foundations still matter in does traditional SEO still matter for AI search?
Our SEO services cover AI search as part of one integrated programme. Get a free quote to see how we would organise it for you.
Related Guides
- Does Traditional SEO Still Matter for AI Search? What the Evidence Shows
- AI Search Myths: 15 Claims That Don't Hold Up
- AI Search Manipulation: Spam Tactics and Prompt Injection to Avoid
Frequently Asked Questions
Is GEO the same as SEO?
Not identical, but heavily overlapping. Google says optimising for its generative AI features is still SEO; GEO adds AI-specific measurement and more emphasis on brand mentions and answer accuracy.
What is the difference between AEO and GEO?
AEO focuses on being the direct answer to a question, while GEO focuses on visibility and citation in AI-generated responses. In practice the terms are often used interchangeably.
Do I need a separate GEO agency?
Usually not. Most GEO work overlaps with SEO, content and PR. Choose a provider that integrates AI visibility into one programme.
Does the GEO research paper prove a 40% uplift?
No. The 2023 GEO paper reported up to 40% higher visibility on its own benchmark. Real-world results on live AI products vary and are not guaranteed.
Which metrics are unique to AI search?
Mention rate across prompts, citation share, share of voice versus competitors, sentiment, factual accuracy and AI referral traffic.
References
- GEO: Generative Engine Optimization (Aggarwal et al., KDD 2024) — arXiv
- Google's guide to optimizing for generative AI features on Google Search
- AI features and your website — Google Search Central
- Traditional SEO vs. AI SEO: What You Actually Need to Know — Semrush, Nov 2025
- Only 22% of marketers have fully integrated AI search and SEO [Study] — Semrush, June 2026
