Key Takeaway
ChatGPT, Perplexity and Gemini give different answers about your brand because each searches a different index, runs on a model with its own training cutoff, decides for itself whether to search, samples its wording with some randomness, and may tailor answers to the person asking.
You ask ChatGPT about your company and get a confident, accurate summary. You ask Perplexity the same thing and your top competitor comes first. Gemini mentions a product you discontinued last year. None of the three is broken. Each one is assembled from different parts, and each part can change what it says about you. This explainer separates the causes, shows how to tell which one you are looking at, and explains what you can actually do about it.
The Short Answer: Different Evidence, Different Writers
ChatGPT, Perplexity and Gemini disagree about your brand because they are not looking at the same evidence, and they are not writing with the same model. An AI answer is the output of a chain: a model decides whether it needs fresh information, a search system fetches pages from its own index, and the model writes a reply from whatever it read plus whatever it learned in training. Every link in that chain differs between products.
That means disagreement is the normal state, not a fault. The useful question is which link is causing the difference you see, because each one has a different fix, and some have none. Our explainer on what AEO means in AI describes the pipeline itself; this article is about why the pipelines produce different results for the same brand.
If you want to see the differences for your own company, the free AEO Grader scan gives a baseline in about a minute from one Gemini check grounded in Google Search, with an estimated view of the other engines. To see each engine's real answer, you need to query each engine, which is covered at the end.
Cause 1: Each Engine Searches Its Own Copy of the Web
There is no single shared web index behind AI answers. Each company runs, or relies on, its own. OpenAI uses OAI-SearchBot for ChatGPT's search features, and its crawler documentation says sites opted out of that bot will not be shown in ChatGPT search answers. Perplexity's crawler page says PerplexityBot is designed to surface and link websites in Perplexity's search results. Anthropic says disabling Claude-SearchBot prevents its system from indexing your content for search. Gemini, by contrast, can draw on Google: Google's developer documentation describes grounding with Google Search as connecting the model to real-time web content.
Each index visits pages on its own schedule and makes its own choices about what to keep. If you changed your pricing page last week, one index may hold the new version while another still has the old one. If a firewall or robots.txt rule blocks one crawler but not the others, one engine loses sight of your site entirely while the rest carry on. The same brand, seen through four separate collections of pages, produces four different stories.
Cause 2: Training Cutoffs Versus Live Retrieval
Every model also carries knowledge from training, frozen at a cutoff date. OpenAI's model page lists an October 1, 2023 knowledge cutoff for GPT-4o, for example. Anything that happened to your business after a model's cutoff is invisible to it unless the system searches. A rebrand, a new product line, a merger or a change of location can all be missing from what a model "remembers".
Live retrieval is the patch for this gap. Google states that search grounding lets Gemini provide more accurate answers and cite verifiable sources beyond its knowledge cutoff. But retrieval only helps when it runs, and when the pages it finds state the new facts clearly. When an engine answers from memory, you get the brand as it looked at training time; when it searches, you get the brand as its index sees it today. Two engines with different cutoffs and different search habits can therefore describe two different eras of your company in the same week.
A practical tell: if an answer contains facts that were true a year or two ago and no source links, it was probably written from training data rather than a fresh search.
Cause 3: Each Engine Decides Whether to Search
Search is not automatic. In every major API, the model itself judges whether a question needs fresh information. OpenAI's web search guide says the model can choose to search the web or not based on the content of the prompt. Google's grounding documentation says the model analyzes the prompt and determines if a Google Search can improve the answer. Anthropic's web search tool documentation says Claude determines when to search based on the prompt.
The consequence for your brand is easy to miss. A question such as "what does Acme do?" can look settled to one model, which answers from memory, and current to another, which searches and finds your new homepage. Phrasing tips the balance: words like "today", "this year", "pricing" or "reviews" make a search more likely. When you compare engines, note whether each answer cites sources. An answer with no links and an answer with five links are not the same kind of evidence, even when they are about the same company.
Cause 4: The Same Engine Varies From Run to Run
Even one engine does not give one answer. Language models choose each word from a range of likely options, and the serving infrastructure adds variation of its own. The team at Thinking Machines Lab, writing about defeating nondeterminism in LLM inference, observes that asking ChatGPT the same question multiple times provides different results, and that LLM APIs are still not deterministic in practice even when temperature is turned down to zero.
For brand monitoring this matters more than it first appears. A shortlist of five vendors might include you in one run and swap you for a rival in the next. A search might return a slightly different set of pages, which changes which facts get quoted. So some of what looks like disagreement between ChatGPT and Gemini is really disagreement between two samples, and it would appear even if you asked the same engine twice. The cure is repetition: ask the same question several times and judge the pattern, not any single reply.
Cause 5: Personalization, Location and Wording
Consumer assistants increasingly adapt to the person asking. Google announced in August 2025 that the Gemini app can reference past chats to learn your preferences, with that setting on by default, and Anthropic's help center says Claude's memory is on by default for Free, Pro and Max plans. Location plays a part too: OpenAI's web search guide lets developers pass an approximate user location to refine results. A logged-in founder, a prospect in another city and a colleague with a long chat history can all get different answers.
Wording is the last variable. Google explains on its AI features page that AI Overviews and AI Mode may run a query fan-out, issuing multiple related searches across subtopics. A small change in your question changes those hidden searches and the pages they return. The table below summarises all five causes and how to spot each one.
| Cause | What you see | How to check it yourself |
|---|---|---|
| Different index | One engine cites your site, another never does | Compare cited domains; check robots.txt and firewall rules for each search crawler |
| Training cutoff | Old facts with no source links | Ask a dated question that forces a search and compare |
| Search decision | Some answers cite sources, others do not | Add words like "this year" or "pricing" and rerun |
| Run-to-run variance | You appear, then vanish, on the same prompt | Run each prompt three or more times and count |
| Personalization and wording | Your answer differs from a colleague's | Repeat in a logged-out session with identical wording |
What You Can Do About It
You cannot make four engines agree, and you should not try to tune your site for one of them at the expense of the others. What you can do is make the evidence about your brand so consistent and so easy to reach that every pipeline, whatever its index, cutoff or search habit, lands on the same facts. The steps below address the causes you control and help you live with the ones you do not.
- ✓Allow every AI search crawler you want to appear in: OAI-SearchBot, PerplexityBot, Claude-SearchBot and Googlebot, and check your firewall as well as robots.txt.
- ✓State your core facts in plain sentences on your own site: what you do, who for, where, and since when. Date announcements so retrieval can tell new from old.
- ✓Make those facts identical on every profile and directory, so no index holds a contradicting version.
- ✓Earn mentions on the third-party pages engines cite in your category, since that is the evidence they read when they search.
- ✓Judge each engine on repeated runs in a clean session, never on a single answer.
- ✓Track each engine separately over time; a drop on one engine points to that engine's index or crawler.
See Every Engine's Answer Side by Side
Doing all of this by hand means four engines, a dozen questions and several runs each. The $10 AEO Grader report does the asking for you. It sends the same panel of buyer questions to ChatGPT, Claude, Perplexity and Gemini through their APIs, with each engine's live web search switched on and no chat history attached, so the differences you see come from the engines rather than from your account. The report shows each engine's actual answer to every question with the sources it cited, engine by engine, so you can compare them directly.
Alongside the answers you get visibility and share of voice for each engine, a count of how often each engine cited your own site, the domains cited most often, and a site audit with a prioritized fix list. If an engine describes a different company with a similar name, the answer is labelled rather than counted as a mention of you. One re-scan within 14 days is included. Like any single panel run, it is a careful snapshot rather than a guarantee of what every future answer will say.
If you would rather start with one engine, our step-by-step guide to checking whether ChatGPT recommends your business shows how to test it manually. Otherwise, run the free AEO Grader scan for a baseline and read the methodology to see how the score is built.
Frequently Asked Questions
Why does ChatGPT say something different about my company than Gemini?
They read different evidence. Each engine searches its own index, relies on a model with its own training cutoff, and decides for itself whether to search at all. If one engine answers from memory and the other finds your current website, they will describe your company differently.
Why does the same AI give a different answer every time I ask?
Language model output is not deterministic. Each reply samples its wording, searches can return slightly different pages, and serving systems add variation of their own. Ask the same question several times and judge the overall pattern rather than any single answer.
Which AI engine is right about my brand?
None of them is authoritative. Each answer reflects the evidence that engine found and when its model was trained. Treat any wrong statement as a signal: find the page it relied on, correct the facts there and on your own site, and check the answer again later.
Can I make every AI engine say the same thing about my brand?
Not exactly, but you can narrow the gaps. Let every AI search crawler reach your site, state your facts clearly and consistently everywhere they appear online, and earn coverage on the sources engines cite. Consistent evidence produces more consistent answers.