How LLMs generate answers: a 2026 guide for marketers

Why marketers should understand how LLMs work

To do generative engine optimization (GEO) well, you need to understand how AI generates its answers. Just as you can't fight an opponent you don't know, you can't optimize for AI without knowing how it works.

Without getting too technical, this article explains how LLMs work, covering what you need for day-to-day marketing.

What is a large language model (LLM)?

A large language model (LLM) is an AI model that has learned the patterns of language from huge amounts of text. It is the technology behind ChatGPT (the GPT series), Gemini, Claude, and Perplexity.

In a nutshell, an LLM generates natural text by repeatedly predicting the most likely next word (token).

An everyday analogy

Think of the predictive text on your smartphone keyboard. When you type "Today's weather is," it suggests words such as "sunny," "cloudy," or "rainy." An LLM does the same thing in a far more sophisticated way, at the level of whole passages of text.

When someone types "What sleep products do you recommend?", the LLM draws on patterns related to "sleep products" in its training data and builds the most natural, relevant answer by generating it one word at a time.

How LLMs are trained: three phases

Phase 1: pre-training

LLMs are trained on huge amounts of text from the internet (websites, books, research papers, news articles and more). At this stage, the LLM:

Learns grammar and the structure of language
Acquires knowledge on a wide range of topics
Learns which expressions fit which context

What this means for marketers: How much information about your brand is in the data learned at this stage directly affects AI answers. If your brand is mentioned often, and positively, on the web, that is more likely to be reflected in AI answers.

Phase 2: fine-tuning

Pre-training alone does not make an LLM return useful answers. To teach it to answer questions accurately, it receives additional training based on human feedback.

What this means for marketers: Because this stage shapes what counts as a "useful answer," AI goes beyond listing information and offers recommendations and advice that match the intent of the user's question.

Phase 3: real-time information retrieval (some AI services)

Some AI services, such as ChatGPT with web browsing and Perplexity, search the web in real time and retrieve the latest information when they generate an answer.

What this means for marketers: Your latest press releases, blog posts, and reviews may show up in AI answers right away. That is one reason why publishing content continuously matters.

How AI chooses which brands to mention

When asked "What project management tools do you recommend?", AI is thought to choose brands through a process like this:

1. Recognizing the topic

First, it recognizes the topic of the question (project management tools) and "activates" the related knowledge.

2. Generating candidate brands

It comes up with candidate brands that are strongly associated with that topic in its training data. Here, how often each brand appears in the training data, in what context, and with what reputation all play a role.

3. Filtering and ranking

From those candidates, it picks the brands that best match the intent of the question and puts them in order. Brands recommended by highly trusted sources tend to rank higher.

4. Writing the answer

It writes the answer, working the selected brands into natural sentences. The brand mentioned first is often the one the AI judged most worth recommending.

For more detail, see how AI search decides which brands to recommend.

Understanding hallucinations

LLMs are subject to a phenomenon called "hallucination." This is when AI generates information that isn't based on fact as if it were fact.

Impact on marketing

Positive impact: If there is enough information about your company, AI will describe your brand accurately
Negative impact: If information is lacking, AI may generate inaccurate information (for example, describing features that don't exist or confusing you with a competitor)

What to do

Publish accurate and consistent information about your company across many sources
Put clear, structured product and service information on your official website
Check AI answers regularly to make sure they are not generating inaccurate information

How the wording of a prompt changes the answer

Even on the same topic, AI answers can change a lot depending on how the user words the question (the prompt). Here are the patterns marketers should understand (the example prompts are translated from Japanese):

Open-ended questions

With broad questions such as "What X do you recommend?", well-known brands tend to be mentioned ahead of others.

Conditional questions

With conditional questions such as "What X works for small teams?" or "What X is available for under ¥50,000?", niche brands also have a chance.

Comparison questions

With comparison questions such as "Which is better, A or B?", AI tends to weigh the pros and cons of both brands objectively.

Knowing these patterns helps you decide which keywords (question patterns) to target in your GEO work.

Training data cutoffs and updates

LLMs have a "training data cutoff date." This is the latest point in time covered by the data the AI learned from.

The AI has learned information from before the cutoff date, but anything after it is not reflected (unless the AI can search the web in real time)
The cutoff date differs from one AI platform to another
Models are updated regularly, and their cutoff dates move forward with them

Practical takeaway for marketers: If you launch a new product or rebrand, AI answers may not reflect it right away. AI with real-time search (such as Perplexity or ChatGPT's web search mode), however, reflects changes relatively quickly.

Summary: make LLM mechanics work for your GEO

Once you understand how LLMs work, your GEO can evolve from "creating content blindly" to "strategic initiatives grounded in how AI works".

Here are the key points to remember:

AI generates answers from patterns in its training data → the volume and quality of your exposure on the web matter
AI favors highly trusted sources → strengthening E-E-A-T helps
AI answers change depending on how the question is worded → plan for a wide range of question patterns
AI can hallucinate → publishing accurate information consistently is important

For a more practical understanding, also read 5 basics to know before you start GEO.

To see how ChatGPT, Gemini and Claude answer Japanese users' questions about your brand, contact us.