What Is SEO for AI Called? GEO, AEO, LLMO and AI SEO Explained

Nobody owns the term. Vendors, agencies and researchers use different names for the same work, and none has become the standard. Here is what each label signals.

The differences are mostly framing. A GEO agency and an AEO tool are usually selling the same checks under different names. If you want the full breakdown of how the labels overlap, see AEO vs GEO vs AI SEO or the wider list of AI search acronyms decoded.

What this means for you: pick whichever term your team and buyers already use. Then judge any service by what it actually checks, not by the acronym on the proposal.

GEO

The term GEO was popularized by an academic paper, "GEO: Generative Engine Optimization" (Aggarwal et al., 2023). The authors tested content tweaks on a search engine they built themselves, with the source documents already supplied to the model. That detail matters later, because the paper's headline numbers come from that lab setup.

GEO has a second meaning. Local marketers have long used "geo" for geographic or location-based search. If a vendor says GEO, ask which one they mean. The guide on GEO SEO: generative engines or geographic search covers the split.

AEO

AEO frames AI tools as answer engines: the user asks a question and gets one answer back. The label puts the focus on being named in that answer.

LLMO and AI SEO

LLMO points at the language model. AI SEO is the plainest label: it tells a buyer this is SEO work aimed at AI surfaces. Neither has a formal definition.

The takeaway: none of these terms comes with a rulebook. Each one is a marketing frame around the same underlying mechanics.

The label hides a more useful distinction. Every AI answer passes through up to four stages, and each one has a different owner.

1. Parametric knowledge. What the model knows with no web access, frozen at a training cutoff. OpenAI's model documentation lists a February 16, 2026 knowledge cutoff for the GPT-5.6 family and August 31, 2025 for the Instant path used in ChatGPT. Nothing you publish this quarter reaches this layer.
2. Access. Whether a crawler may fetch and store your page at all. This is the stage you control most.
3. Retrieval. Whether your page enters the model's context for a given question. Engines rewrite the user's prompt into their own search queries, so you can't see the real input.
4. Generation. Which retrieved documents the model uses and cites.

Retrieval is discretionary. As of October 2026, ChatGPT decides per question whether to search, Claude.ai search is a user toggle, and Google AI Overviews often do not trigger at all. So any single visibility number blends answers given with and without live search.

This is why the naming debate is a distraction. A critical survey of 45 GEO studies (arXiv, July 2026) concluded that "already-retrieved content can causally alter its citation or use, but no reviewed technique shows a stable, longitudinal, cross-platform causal effect on organic discoverability." In plain English: tweaks can change how a page is used once it's already in the answer pool. Nobody has shown a tactic that reliably gets you into the pool.

In your control

• Per-bot crawler permission. robots.txt rules apply bot by bot. OpenAI's crawler documentation says GPTBot governs training and OAI-SearchBot governs ChatGPT search, and "each setting is independent of the others."
• Network reachability. A firewall or CDN can block a crawler that robots.txt allows. OpenAI's help centre says eligibility needs both the robots.txt permission and a host that accepts its search crawler's IP addresses.
• Server-rendered content. Vercel's crawler study found ChatGPT and Claude crawlers fetch JavaScript files (11.50% and 23.84% of requests) but don't execute them, so content that appears only after JavaScript runs may be invisible to them. Googlebot does render JavaScript.
• Snippet and index controls. noindex, nosnippet, max-snippet:0 and data-nosnippet keep content out of AI answers on Google and Bing. Google says a page must be indexed and snippet-eligible to appear as a supporting link in AI Overviews or AI Mode, with no additional technical requirements.
• Stating facts plainly. A specific price, number or one-line definition on a fetchable page gives an engine a sentence it can quote.

Not in your control

• What the model learned in training.
• The search queries an engine writes from the user's prompt.
• Where your page sits in the model's context list.
• Whether retrieval fires for a given question.

One area sits in between. When engines cite other sites instead of yours, being named on those sites is associated with appearing in the answer. That is an association in the evidence, not a promised effect.

Whatever you call it, the work runs in the same order: remove blocks first, then make your facts easy to quote, then measure.

1. Read your robots.txt bot by bot. A blanket AI block often removes ChatGPT search eligibility by accident. Training and search bots can be set separately:

User-agent: OAI-SearchBot
Allow: /

User-agent: GPTBot
Disallow: /

2. Test what your firewall actually returns. A 403 to a search crawler is a silent failure. Cloudflare began blocking training and agent crawlers by default on ad-displaying pages for some accounts from September 15, 2026, so a site can lose access without anyone editing it. The AI Crawler Checker requests a page as each AI crawler and shows which ones get turned away.
3. Compare raw HTML with the rendered page. Look for prices, product names and key claims that only appear after JavaScript runs. Content inside tabs and accordions is a common gap: see the tabs, accordions and load more check.
4. Check index and snippet status. Look for stray noindex or nosnippet tags inherited from templates. Check Google Search Console and Bing Webmaster Tools separately, since Bing's index backs Microsoft Copilot.
5. State your key facts once, clearly, and consistently. If your pricing page and footer disagree, an engine may repeat either.
6. Check what each engine says about you. Measure engines one at a time, not as a blended score. The free checker on this site shows whether AI engines name you for up to three buyer questions. A broader free GEO audit follows the same order: access first, then accuracy.

New acronyms attract old advice. These recommendations are widely sold under every label, and primary sources contradict them.

• "Add schema to get cited." Google says structured data isn't required for generative AI search. Ahrefs' matched test of 1,885 pages found AI Overview citations fell 4.6% after schema was added. Existing markup does no harm, but it isn't a lever for AI answers.
• "Publish an llms.txt." Google says Search ignores it, and no other engine documents reading it.
• "Improve your E-E-A-T score." Google says E-E-A-T isn't a specific ranking factor. There is no score to move.
• "Build domain authority." Domain Authority is a Moz metric. No engine computes it.
• "Write in an AI-friendly style" or "chunk your content." Google rejects both and says there's no ideal page length. Offering alternate formats is a related question, covered in should you offer Markdown versions of pages for AI.
• "Allow GPTBot so ChatGPT can find you." GPTBot governs training only. ChatGPT search uses OAI-SearchBot.
• "GEO gets you up to 40% more visibility." The original GEO paper reported a 30 to 40% band in a lab engine with sources already loaded into context. It says nothing about being found on the live web.
• "Track your AI rank." Google's AI report shows impressions only. No position data exists to check such a number against.
• Mass-publishing pages. Volume without value is what Google's spam policies call scaled content abuse. See whether publishing more content helps AI visibility.

Any vendor, whatever acronym they use, who promises citations or a guaranteed score is promising something nobody controls.

Use the term your audience searches for and your team already understands. In practice:

• AI SEO is the easiest sell internally, because it tells stakeholders this builds on existing SEO work.
• GEO is common in research and vendor marketing, but carries the geographic-search ambiguity.
• AEO fits teams focused on question-led content and being the named answer.
• LLMO is less common and leans toward the model rather than search.

Much of the work overlaps with classic SEO: Google says there are no special optimizations needed for AI Overviews or AI Mode beyond normal Search eligibility. The differences show up with non-Google crawlers, which don't render JavaScript and each need their own robots.txt permission. The comparison of GEO vs SEO covers where the two diverge.

The next move: settle on one term in your briefs so nobody thinks GEO and AEO are two separate projects. Then start with the access checks above.