What AI Models Actually Say About Your Business When a Buyer Asks And How to Control It
A potential customer no longer starts their research with a Google search alone. Increasingly, they open ChatGPT, Perplexity, or Gemini and simply ask: “Is [your company] any good?” or “What do people say about [your brand]?” Whatever the model answers in that moment can make or break a deal before your sales team ever gets a chance to speak to the buyer.
This is the reality of AXO — AI Experience Optimization, sometimes called AI Answer Optimization. It’s the practice of understanding, monitoring, and shaping how large language models describe your business, because those answers are quietly becoming as important as your Google ranking, if not more so.
Why AI Answers Matter as Much as Search Rankings
For the past two decades, brand reputation management focused on controlling what appeared on page one of Google: reviews, news coverage, social proof, and your own website. That work still matters, but a new layer has been added on top of it. AI models don’t just show links — they synthesize an opinion. When a buyer asks an AI model about your business, they get a summarized, conversational answer that blends your website copy, review sites, news articles, forum threads, and comparison content into a single narrative.
The problem is that this narrative is often built from outdated, incomplete, or even incorrect information, and most business owners have no idea what that narrative currently says. Unlike a search results page, there’s no simple way to “check your ranking” for an AI answer — you have to actively query the models yourself to find out.
What Determines What AI Says About Your Business
Language models don’t have a live, verified profile of your company. They form impressions based on the volume, consistency, and credibility of information available across the web. Several sources tend to carry the most weight:
- Your own website content, especially the About page, service pages, and any structured data (schema markup) that clearly defines who you are and what you do.
- Review platforms such as Google Business Profile, Trustpilot, Clutch, and industry-specific directories.
- News mentions, press releases, and third-party articles that reference your company by name.
- Comparison and “best of” articles where your brand is discussed alongside competitors.
- Forums, Q&A sites like Quora and Reddit, and community discussions where your brand is mentioned organically.
- Wikipedia and other reference sites, when applicable, which models tend to treat as high-authority sources.
Because AI models pull from this wide mix of sources, a single outdated review, an unresolved complaint thread, or a competitor’s biased comparison article can end up shaping the answer a buyer receives, even if it no longer reflects your business today.
How to Find Out What AI Models Are Saying About You
The first step in AXO is simply auditing your current AI narrative. This means running a consistent set of prompts across the major models your buyers are likely to use, and documenting the answers.
- Ask direct brand questions: “What is [company name]?” and “What does [company name] do?”
- Ask reputation questions: “Is [company name] a good company to work with?” and “What do customers say about [company name]?”
- Ask comparison questions: “How does [company name] compare to [competitor]?”
- Ask buyer-intent questions: “Should I hire [company name] for ?”
Run these prompts across ChatGPT, Gemini, Perplexity, and Copilot at minimum, since each model draws on different training data and live retrieval sources, and their answers can vary significantly. Keep a simple log so you can track how the narrative shifts over time as you make changes.
How to Influence and Control the AI Narrative
Once you know what the models are currently saying, you can start shaping the inputs that feed those answers. This isn’t about tricking an AI model — it’s about making sure accurate, current, and favorable information about your business is the most visible and most consistent information available for it to learn from.
- Strengthen your own first-party content
Make sure your website clearly and explicitly states what your company does, who it serves, and what makes it different, in plain language a model can easily extract. Vague marketing copy gives AI models less to work with than direct, factual statements.
- Use structured data and schema markup
Organization schema, review schema, and FAQ schema give models machine-readable signals about your business identity, offerings, and reputation, which reduces the chance of misinterpretation.
- Actively manage reviews across platforms
Respond to negative reviews professionally and encourage satisfied customers to leave detailed, specific feedback. Models weigh the tone and consistency of review content, not just the star rating.
- Get featured in credible third-party content
Earned mentions in industry publications, comparison articles, and roundups carry more weight than self-published claims. Digital PR and guest content remain some of the most effective ways to influence how models perceive your credibility.
- Correct outdated or inaccurate information at the source
If an old article, directory listing, or forum post contains incorrect details about your business, reach out to have it updated or add a follow-up comment with the correct information. Models can’t always tell the difference between current and stale content unless the correction exists somewhere for them to find.
- Monitor consistently, not just once
AI models update their retrieval sources and training data on an ongoing basis. A narrative that looks accurate today can drift within a few months. Treat AXO monitoring as a recurring task, similar to rank tracking in traditional SEO.
Where AXO Meets Online Reputation Management
AXO and traditional online reputation management (ORM) are converging into a single discipline. ORM has always been about ensuring the internet reflects your business fairly and accurately; AXO extends that responsibility into the layer where AI models summarize that same information for buyers who never click a single link. A business that manages both together — clean, consistent, and accurate signals across the web, paired with active monitoring of AI outputs — is far better positioned to win the buyer’s trust in the moment that actually matters: the moment they ask an AI model whether your business is worth working with.
The Bottom Line
Buyers are outsourcing part of their research and trust-building process to AI models, and those models are forming and repeating an opinion about your business whether you’re paying attention or not. The businesses that get ahead of this now — by auditing their AI narrative, strengthening first-party signals, and treating AXO as an ongoing discipline — will be the ones showing up as the trusted answer instead of the flawed alternative when the next buyer asks.
Traditional SEO focuses on ranking web pages in search engine results so a person clicks through to your site. AXO focuses on how AI models summarize and describe your business directly inside a conversational answer, often without any click at all. The two disciplines share many underlying tactics, such as strong content and credible mentions, but AXO specifically targets how models interpret and repeat information about your brand.
You can’t edit a model’s output directly, but you can influence it by changing the underlying information the model draws from — your website, reviews, press coverage, and structured data. Because models are retrained and refreshed over time, and several also pull live web results, improvements to your public information footprint do eventually show up in how the model responds.
Yes, and often more easily than in traditional SEO. AI trust is built on clarity and consistency, not domain age or marketing budget. A small business with clean schema and accurate, consistent listings can be recommended ahead of a much larger competitor whose information is scattered or outdated.
No it extends it. ORM work such as review management, PR, and correcting inaccurate listings directly feeds into a stronger AI narrative, so the two efforts reinforce each other rather than competing for budget or attention.
No. AIO sits on top of strong SEO fundamentals. You still need a fast, crawlable, well-structured website. AIO adds the trust and clarity layer that helps AI systems confidently recommend that website once it is found.
