What Is AI Search Optimisation Also Known As? GEO, AEO, LLMO and the Other Names Explained

By Yamm Labs · Updated September 2026 · 5 min read

A marketing head at a mutual fund house in Mumbai lays three agency proposals side by side. One sells generative engine optimisation. One sells answer engine optimisation. The third sells LLM optimisation. She assumes she is comparing three different services and asks her team to build a scoring sheet for each. She is not. All three proposals describe the same job: getting the fund house named, described correctly and cited when a buyer asks ChatGPT, Gemini or Perplexity a question. The names differ. The work, and the compliance risk inside it, does not.

What are the other names for AI search optimisation?

Five names cover almost every proposal an Indian BFSI marketer will see. They overlap heavily, and agencies often use two or three of them on the same page.

Our AI search optimisation hub of 100 questions holds the one-paragraph version of this answer next to related questions on measurement and regulated brands.

Where did the term generative engine optimisation come from?

GEO entered wide use through a research paper titled GEO: Generative Engine Optimization, first posted on arXiv on 16 November 2023. The authors described generative engines as systems that use generative models to gather and summarise information to answer a query, and reported that their methods raised a source’s visibility in those answers by up to 40% in their own tests. They also found that what works varies by domain. That finding matters for financial brands: a tactic that lifts a travel blog may be one a compliance desk would never approve for a lending app.

Is AI search optimisation a separate discipline from SEO?

Not in Google’s view. Google’s guidance for site owners says there are no additional requirements and no special optimisations needed to appear in AI Overviews or AI Mode, and that SEO best practices still apply. It also says no new machine-readable files, AI text files or special schema are needed. A page has to be indexed and eligible to show a snippet in normal search.

So the renaming is about emphasis, not a new rulebook. What GEO, AEO and LLMO add on top of SEO is a way of writing and a way of measuring: answer-first passages that stand alone when quoted, consistent facts about the brand across the web, and a monthly check of what each engine says about you.

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What changes when a bank, insurer or fund does AI search optimisation?

An engine lifts a passage, not a page. Whatever sits in a footer or a separate disclaimer box may never travel with the quote. That single fact drives the design decisions a regulated brand has to make, whatever the agency calls the service.

• The disclaimer sits in the quotable passage. If a paragraph about a mutual fund could be lifted whole, SEBI’s standard mutual fund risk warning belongs inside that paragraph, not in a footer. SEBI has long required that warning in fund advertisements and, for audio-visual ads, requires it to be displayed and voiced for at least five seconds. The written equivalent is keeping it next to the claim it qualifies.
• The registered name travels with the brand name. IRDAI’s current rules require an insurer’s advertisements to carry its registered name, shown prominently alongside any trade name or logo. On an answer page, that means the legal name appears in the same sentence an engine would quote as the product name.
• Key terms come before the form. IRDAI’s rules bar insurance advertisements that obscure terms and conditions or disclose important exclusions and limitations insufficiently. On an answer page, the exclusions paragraph sits above the quote button, not below it.
• A named reviewer signs off before publishing. Our AI visibility programme for BFSI brands does not run GEO for a regulated brand without a named compliance reviewer on the client side.

Call it GEO, AEO or LLMO; the engine will quote the paragraph, so the paragraph must carry its own disclaimer.

A short glossary of AI search optimisation terms

Proposals for GEO, AEO and LLMO borrow the same small vocabulary. Knowing these terms makes it easier to see that three differently named services describe one piece of work.

• Generative engine: a system that uses a generative model to gather information and write an answer, such as ChatGPT, Gemini or Perplexity. This is the “G” in GEO.
• Answer engine: any system that returns a direct answer rather than a list of links, including featured snippets and voice answers. This is the “A” in AEO.
• Citation: a link or named source shown alongside an AI answer. Being cited is the goal most GEO work reports on.
• Passage: the paragraph or table row an engine lifts into its answer. Search optimisation for AI works at this level, not at the level of the whole page.
• Entity consistency: the brand name, product names and key facts matching across your site and third-party pages, so engines describe the brand the same way everywhere.
• Buyer prompt: a question a real buyer types into an engine. A fixed list of these is the basis of any honest measurement.

Common mistakes when comparing AI search optimisation proposals

The marketing head in the opening nearly made the first mistake on this list. The others follow from it.

Scoring the name instead of the work. A GEO proposal and an AEO proposal can describe the same tasks. Put every proposal into one scoring sheet built on the work: access, answer-first writing, entity consistency, measurement and compliance review.

Buying a new rulebook. Google says no special optimisations, AI text files or special schema are needed to appear in AI Overviews or AI Mode. A proposal built mainly around new files is selling something the engine’s own guidance says you do not need.

Accepting results without a baseline. Without a fixed list of buyer prompts run before the work starts, there is nothing to compare later results against. Ask for the baseline first.

Ignoring the disclosure. For a fund house, a quoted passage that loses SEBI’s risk warning is a compliance problem, whatever the service is called. A proposal that does not say where the warning sits in each passage has missed the main BFSI risk.

Borrowing tactics from other sectors. The GEO paper found that what works varies by domain. A tactic that helps a travel blog may be one your compliance desk would reject. Ask for examples from regulated brands.

A worked example: one scoring sheet for three proposals

Here is how the fund house could compare its three proposals once it accepts that GEO, AEO and LLMO describe the same job.

Step one, one sheet. The team builds a single sheet with the same rows for every proposal: which engines are tested, how many buyer prompts are tracked, how results are scored, how often they are re-run, and who reviews each page for compliance.

Step two, fill it from the proposals. Each agency’s answers go into the same rows, whatever name sits on the cover. Gaps show up quickly. One proposal may track engines but not name a compliance reviewer. Another may promise answer-first rewrites but say nothing about measurement.

Step three, ask for one page. Each agency is asked to show one page where a regulator’s rule changed the layout, for example where the risk warning moved from the footer into the quotable paragraph.

Step four, choose on the work. The fund house picks the agency whose sheet is complete and whose page example is credible. It then writes its own brief using the term its leadership already knows, and defines the work underneath it.

Questions to ask any agency, whatever it calls the service

These questions work for a GEO, AEO, LLMO, AI SEO or AI visibility proposal. They test the work, not the label.

1. Which buyer prompts will you track, and can we add our own?
2. Which engines will you test, and how often?
3. How do you score a result, and will we see the raw answers?
4. What will you change on our site first, and why?
5. Where will the regulator’s disclosure sit in each quotable passage?
6. Who on our side reviews each page before it goes live?
7. Can you show one page where a compliance rule changed the design?

An agency that answers these clearly is doing AI search optimisation, whatever it calls it. Regulatory points here are general practice; confirm the current text with your compliance team before you brief.

Which name should a BFSI buyer use in a brief?

Use the name your leadership already understands, and define the work underneath it. A good brief names the buyer questions to track, the engines to test, how results are scored and who on your side reviews each page for compliance. Our own programme tracks 20 buyer prompts across six engines, ChatGPT, Gemini, Perplexity, Google AI Mode, Microsoft Copilot and Claude, and scores each result Present, Partial or Absent. Whatever the proposal calls itself, ask to see that measurement sheet and one page where a regulator’s rule changed the layout.

Yamm Labs works from Gurugram and serves BFSI clients across India, with Gulf and international work handled remotely. The GEO and AEO FAQ for financial brands covers the follow-on questions on scope, measurement and timelines.

People also ask

Is GEO the same as AEO?

Mostly, yes. GEO stresses engines that write a full answer, while AEO stresses direct answers such as featured snippets and voice results. Buyers use the terms interchangeably, and one programme usually covers both.

Is AI SEO different from normal SEO?

It builds on it. Google says no special optimisation is needed to appear in AI Overviews or AI Mode beyond SEO best practices, so AI SEO adds answer-first writing and monthly tracking of what engines say rather than a separate rulebook.

Does a regulated financial brand need a different kind of AI search optimisation?

It needs the same work with one extra rule: every passage an engine might quote must carry its own disclosure. On an AI-ready page, SEBI’s risk warning, an insurer’s registered name and key exclusions belong inside the quotable text, not in a footer.

What does LLMO stand for?

LLMO stands for LLM optimisation, or large language model optimisation. It stresses the model itself and what it has learned about a brand. In practice, LLMO proposals cover much of the same work as GEO and AEO: clear, consistent facts about the brand and answer-first passages an engine can quote.

Is AI visibility a service or a metric?

Both, depending on who uses it. In boardrooms and scorecards it usually means the outcome: whether the brand shows up in AI answers at all. Some agencies also sell AI visibility as a service name. Either way, ask how it is measured, with which prompts and on which engines.

Why do agencies use different names for AI search optimisation?

Partly history and partly positioning. GEO came into wide use through a 2023 research paper. AEO grew out of work on featured snippets and voice answers. AI SEO lets an SEO agency extend an existing retainer. The names signal where an agency came from more than what it will do.

Does the name on the proposal change the price?

It should not. Price should follow the work: how many pages need rewriting, how many prompts and engines are tracked, and how much compliance review each page needs. If two proposals describe the same work under different names, compare them on the work.

Is AI search optimisation only about ChatGPT?

No. ChatGPT is the engine most buyers name first, but the work covers every engine that writes answers. Our own tracking covers six: ChatGPT, Gemini, Perplexity, Google AI Mode, Microsoft Copilot and Claude. Each one retrieves and credits sources in its own way, so a brand that appears in one answer may be missing from another. Track the engines your buyers actually use.

Can an in-house team do this work without an agency?

Yes, if the right people are involved. The work needs someone who can change crawler rules and page templates, writers who can produce answer-first passages, and a compliance reviewer who approves disclosure blocks once so they can be reused. A sensible route is to start in-house with a fixed prompt list and a monthly check, then bring in outside help for the rewrite only if the baseline shows large gaps across several engines.

Will one of these names replace the others?

Nobody can say yet, and it matters less than it seems. The engines do not care what the work is called. What decides whether your brand is named and quoted is the page itself: crawlable, answer-first, consistent with the rest of the web and, for a financial brand, carrying its disclosure in every quotable passage.