Can You Train AI to Recommend Your Business? What Is Actually Possible

You cannot train public AI assistants like ChatGPT, Gemini, Claude or Copilot to recommend your business. Their makers train the models on large datasets, and no outside business controls that process or can pay to be added. What you can do is publish clear, accurate, widely referenced information, so that both live web searches and future models have good material about you.

What “training” really means

A large language model is trained once on huge amounts of text, then refined by the company that builds it. After training, the model has a fixed knowledge cutoff. Chatting with an assistant and telling it “recommend my bakery” does not retrain the public model for other users. At most, some assistants offer personal memory features that affect your own account only.

The part you can influence: live retrieval

Many assistants now search the web while answering. Perplexity shows its sources. ChatGPT can browse. Copilot uses Bing. Google AI Overviews draw on Google Search. When they search, they read current pages. This is where your work has the most direct effect:

• Pages that answer buyer questions directly
• Accurate, consistent facts across your site and profiles
• Independent mentions in reviews, directories and articles
• Technical access so crawlers can read your pages

The slower part: future training data

Model makers often use public web content as part of their training data, subject to their own policies and site owners’ crawler settings. Good public content about your business may become part of what future models learn. But you cannot know or control whether a specific page is included, and anyone who promises to “put you in the training data” is overstating what they can do. Our page on content and AI training data covers this in more detail.

A practical way to think about it

Instead of “training the AI”, think of “teaching the web”. If ten independent, credible sources say that your firm is a specialist in commercial roofing in Toulouse, and your own site says the same clearly, any system that reads the web, now or later, has good reasons to connect you with that topic.

Five things to do this month

1. Write a one-sentence description of what you do, for whom and where. Use it everywhere.
2. Create one strong page for each main service, starting with a direct answer.
3. Check that robots.txt does not block search engines or the AI crawlers you want to allow.
4. Claim and complete your main directory and map profiles.
5. Ask recent customers for honest reviews.

Myths to ignore

• “Ask ChatGPT about your brand many times and it will learn.” It does not work that way for the public model.
• “Post hundreds of forum comments so the AI picks you up.” This is spam and can harm your reputation.
• “Pay to be in the model.” There is no such product from AI companies.

For how models pick names in practice, see how LLMs choose brands.

What about custom GPTs and chatbots?

You can build your own chatbot or custom assistant that knows your products, for use on your website or by your team. That is a useful tool, but it only affects that bot. It does not change what the public ChatGPT or Gemini tells other users. Keep the two goals separate when planning budget.

How Keboost helps

Keboost focuses on what you can influence. It tracks the prompts your customers ask across AI models, shows where you and your competitors appear, and creates and distributes focused content so assistants can find and cite you. Run a free AI visibility check to see where you stand.