Not on its own. AI doesn’t know how old your company is unless its footprint online says so: the website, the Google Business Profile, directories, reviews and publications. And AI judges that footprint not by the date the company was founded, but by how fresh it is and whether it is tied to the city where the customer is searching. We saw this in measurements of one local market in Poznań, and large US studies show the same picture across millions of AI answers.
20 years in business ≠ 20 years that AI can see.
In one market, the older company almost disappeared from AI answers, while the younger one began to appear twice as often
For one of our projects — a local service business in Poznań — we asked four systems (ChatGPT, Gemini, Perplexity and Google AI) the same 14 questions three times, in July, August and September 2026: the questions a customer asks when looking for such a business in their city. That is 56 answers per measurement. Among the companies the systems named were two whose start dates are known.
The first has been operating since 2015. It has a large website with a separate page for Poznań, a blog and more than 2,000 Google reviews. In July, AI named it in 20 answers out of 56. In August, in one answer out of 56; in September, in four.
The second has been operating since the end of 2023, so for less than three years. It has no blog, but it does have up-to-date profiles on local platforms with reviews and listings. In July, AI named it in 13 answers out of 56, in August in 23 and in September in 27.
Eleven years of work and thousands of reviews did not keep the first company in the answers. Less than three years did not stop the second from becoming, within two months, one of the most frequently named companies in this market.
AI sees not a company’s age but its footprint: how fresh it is and which city it belongs to
When someone asks AI about a service in their city, the system builds its answer from what it finds online at that moment. The founding year is just another fact to it: it only counts if it is written down somewhere and linked to the company. Twenty years of experience that live in customers’ memories but never made it online do not exist for AI.
You can also see this in how AI describes the company from our project. When we asked about it by name, three of the four systems — ChatGPT, Perplexity and Google AI — gave the year it started, 2024, and took it from exactly where it is written: the company’s website and a directory where it has a profile. One of the systems put it plainly: “the company states that it has been operating since 2024”. The system doesn’t care how old the company really is. It repeats what has been written about it.
The first company has one more detail. Its Google Business Profile, with all its reviews, is registered in Warsaw, and it has no profile in Poznań. For a question about such a business in Poznań, its experience and reviews turned out to be tied to another city. We can’t claim this is the reason for the drop: it is a single observation. But it shows the key point — a company’s maturity does not turn into a recommendation by itself.
Large studies: AI relies on pages a year younger than those in Google results
A US study that analysed 17 million links from AI answers found that the average age of pages cited by AI assistants was 2.9 years, compared with 3.9 years in regular Google results. ChatGPT leans most strongly towards fresh pages.
Another US study looked at server logs: 89% of visits by ChatGPT’s bots went to content updated within the last three years, and only 6% to content older than six years.
Neither study measures the age of the company itself. They measure the age of pages. To AI, a company is “old” exactly as far as its online footprint is old, and “experienced” exactly as far as that experience has been described. Our local Polish observation points in the same direction.
For a mature company, its history is a reserve that still has to be moved online
If a company has been operating since, say, 2006, nobody back then expected a local business to document its history online. That is why many mature companies have deep experience but a digital footprint that is short, outdated or recorded somewhere other than where customers search. This is not a flaw in the business; it is a gap between its real history and the part of it that AI can find.
The good news is that a mature company has material a young one doesn’t: years of work, thousands of completed jobs, loyal customers. The only question is how much of this has made it online, whether it is tied to your city and whether it has been updated in recent years.
When this isn’t the main question
If your customers come only through referrals and regular partners, and you don’t need new work right now, the gap between your experience and your digital footprint can wait. And the other way round: a young company doesn’t need to wait until it turns ten. It has access to the same thing as an old one — a fresh, clear footprint tied to its own city.
And the limits of our data: this is one market, one city, two companies with a known start date and three measurements. It is an observation, not a law of the market.
How to check your own company
Ask ChatGPT and Gemini: “Since what year has [company name] in [your city] been operating, and what is known about it?” Compare the answer with reality: do the year, the city and what you do today match?
If AI tried to reconstruct your company’s history from the internet today, what would it find — and in which city?
Sources: Study of 17 million links in AI assistant answers and the freshness of cited pages (2025); Study of server logs and AI citations by content freshness (2025).
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