Big AI companies are spending far more money than they are earning back.
ChatGPT often picks brand names to recommend before it even searches
the internet.
Being remembered early makes a brand about 33 times more likely
to get mentioned.
This system quietly favors big,
already-famous brands over new or
small ones.
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Every big AI company has poured enormous amounts of money into building tools like ChatGPT. But most of them are still losing money on every single answer they give. Some are spending more than a dollar for every dollar they earn back. That is not a small problem. That is the kind of number that makes people nervous about how long this can continue.
Many in the industry are now calling this the early sign of an AI recession, a slowdown after years of companies spending huge amounts of money without seeing it paid back yet.
When a company is losing money on every answer, it looks for every possible way to cut cost and prove its product is worth using. This pressure directly shapes how tools like ChatGPT behave when you ask them a question, including which brands they choose to talk about.
Here's where it gets serious. Before ChatGPT even searches the internet to answer a question like "best AI note-taking app," it already writes a few brand names into its own private search. Names like Granola, Notion AI, or Otter show up, even though nobody typed them.
These are not random guesses. ChatGPT learned these names while reading huge amounts of text from the internet during its training. If a brand's name appeared often enough, next to its category, in blogs and reviews, ChatGPT remembers that pairing and leans on it first, before doing any
real search.
Once a brand is remembered this way, the numbers behind this idea show it becomes about 33 times more likely to be mentioned in the final answer. If a brand was never talked about enough online to be remembered, it barely stands a chance of being mentioned at all, no matter how good the product actually is.
Famous, heavily reviewed brands get remembered easily, and get mentioned more often as a result. This extra visibility often leads to even more reviews and mentions being written about them later, which keeps reinforcing their position again and again. New or small brands are left standing outside this loop.
Not really, and there are two sides to see here.
It is fair in the sense that ChatGPT isn't secretly taking money to favor one brand over another. What it recalls comes from how much a brand was talked about online, not from a
paid deal.
It is unfair in the sense that a brand's true quality today has very little say in the matter. A brilliant new product can be invisible simply because it wasn't talked about enough while ChatGPT was learning. Meanwhile, an older, average product can keep getting recommended purely on reputation built years ago.
If money pressure keeps building on AI companies, and fairness keeps tilting toward already-famous brands, the businesses that protect themselves are the ones building real visibility outside of AI too, through genuine reviews, comparisons, and honest coverage across the web. That kind of visibility can't be bought overnight, and it's exactly what decides whether AI remembers you at all.
We have already shown this working with real numbers, not just theory, in our earlier post on why organic SEO still grows business even when a brand is missing from AI Overviews.
AI companies are burning far more money than they are making, and many are now calling this the start of an AI recession. This money pressure shapes how tools like ChatGPT answer questions, because they often recommend brand names they already remember from training, before ever searching the internet. This quietly favors big, well-known brands and leaves new or smaller ones with little chance of being noticed, unless they get talked about and reviewed across the web over time. That is the real story behind AI fairness today.
Disclaimer :
AI company finances and product behavior change fast. This post reflects the situation as understood when it was written. Always check current numbers before making a business decision based on this.
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