How often AI recommendations change

Published

By Carson Cobb. Data collected November 2026.

“ChatGPT recommended us yesterday and not today.” I hear some version of this all the time. AI answers are written fresh every time, so some change is guaranteed. The useful question is how much, and where in the list.

So I asked ChatGPT the same 12 buyer questions 4 to 5 times each, in fresh temporary chats, across two days. That’s 55 answers, and I tracked every brand named in each one.

The short version

  • The first pick almost never moves. The brand named first came back in 98% of the other runs of the same question.
  • Position decides stability. Second place came back 93% of the time, third 74%, fourth 65%, and fifth or lower 56%.
  • The same top pick in every run for 10 of 12 questions. In the other 2, two brands traded first place.
  • Only 40% of brands were named in every run. 19% appeared only once.
  • Wording matters more than randomness. Rewording the question changed the list far more than asking it again did. See how question wording changes AI recommendations.

Stability by position

For every brand in every answer, I checked whether it was named again in each other run of the same question.

Position in the answerNamed again in another run
1st98%
2nd93%
3rd74%
4th65%
5th or lower56%
Any position77%

The drop after second place is the important part. Positions 1 and 2 are close to locked. From position 3 down, a brand’s presence is closer to a coin flip than a guarantee.

How the lists changed

Across the 12 questions, ChatGPT named 83 different brands at least once.

BrandsShare
Named in every run3340%
Named in some runs3441%
Named in only one run1619%

Two runs of the same question shared, on average, 66% of the brands either of them named. That sounds low, but it’s much higher than the overlap between different AI tools for the same question, which was 39% to 45%. See ChatGPT vs Gemini vs Google AI Mode.

List length moved too. One question about protein powder got 3 brands in one run and 9 in another. A longer list doesn’t push the top brands out. It adds more brands at the bottom, and those are the ones that come and go.

Top picks

QuestionsSame top pick in every runTop pick changed
12102

The brand named first most often held first place in 52 of 55 answers. In both questions where first place changed hands, the two brands trading places were each named in at least 4 of 5 runs. The top of the list rotates between a small set of strong brands. It doesn’t jump to brands that were barely there.

Growing brands held their spots about as well

24 of the 83 brands have their own Shopify store and appear in my dataset of growing US brands. 11 of them (46%) were named in every run they could have been, against 22 of 59 (37%) for every other brand. Being a smaller brand did not make a spot less stable. Position did.

What this means for checking your own visibility

  1. One answer is not a result. Ask the same question at least three times, in fresh temporary chats, before you decide whether you’re recommended.
  2. Record the position, not just yes or no. Position 1 or 2 is a strong signal. Position 4 means you’re in the part of the list that changes between conversations.
  3. Count how often, not whether. “Named in 3 of 5 runs” is a far more honest number than a screenshot.
  4. Moving up beats getting in. Going from fifth to second matters more than going from absent to fifth, because fifth comes and goes.
  5. Compare like with like over time. Same questions, same number of runs, fresh sessions each time. That’s the only way a month to month change means anything.

This is how I track products for clients: the same buyer questions, repeated runs, positions recorded, on ChatGPT, Gemini and Google AI Mode. See the AI Search and Conversion Audit, or start with the free AI Visibility Check.

How this was done

  • Questions: 12 of the 48 buyer questions from Who ChatGPT recommends, across apparel, beauty and skincare, food and beverage, home, pet and supplements.
  • Runs: 4 or 5 runs per question, 55 in total. The first run of each question and a repeat of some questions on November 4, 2026, and three more runs on November 5, 2026.
  • How they were asked: ChatGPT on a paid plan, default model and default thinking setting, each run in a new temporary chat.
  • Brands: every brand named in an answer as an option to buy, in order of first mention, matched against a list of known brands and aliases for each question and checked by hand.
  • Named again: for each brand in each run, the share of the other runs of the same question that also named it.
  • Limits: two days of data on one AI. Stability over months will be lower, and Gemini and AI Mode may behave differently.

No store or brand is named in this report.

FAQ

Questions, answered.

Does ChatGPT give the same recommendations every time?

The top of the list is very stable and the bottom is not. In 55 runs of 12 buyer questions in November 2026, the brand ChatGPT named first came back in 98% of the other runs of the same question. Brands in fifth place or lower came back in only 56%.

How many times should I ask ChatGPT a question to know if it recommends my brand?

At least three times, in fresh temporary chats. A brand named in position 1 or 2 will almost always appear again. A brand in position 3 or lower appeared again only 56% to 74% of the time, so one screenshot can make you look better or worse than you are.

Do the top picks change over time?

Rarely over a few days. The top pick was identical across every run for 10 of 12 questions. In the other 2, two brands traded first place. What changed most was the middle and end of the list.

Why do AI recommendations change between runs?

AI tools generate each answer fresh and run a new web search each time. Small differences in which pages the search returns, and in how the model writes, change the brands near the end of the list most.

See where you stand in AI search.

Run the free AI Visibility Check. In about a minute you'll see whether ChatGPT recommends you, who it recommends instead, and what's holding you back.