Why AI chatbots give wrong answers, and how to stop it

Short answer: AI chatbots give wrong answers mainly because they're built and scored in a way that rewards a confident guess over an honest "I don't know." OpenAI's own researchers found this in a September 2025 study. For a store chatbot, the fix is to restrict it to your actual pages and tell it explicitly that saying "I'm not sure" is an acceptable answer, not a failure.

Facts last checked on October 20, 2026, against the sources linked below.

The actual research, not a guess about it

In September 2025, OpenAI researchers Adam Tauman Kalai, Ofir Nachum, Santosh S. Vempala and Edwin Zhang published "Why Language Models Hallucinate", explaining why models state something false with full confidence. The core finding: models are trained and evaluated like students taking a multiple-choice exam where a guess scores higher on average than leaving the answer blank. Euronews' coverage of the paper put it the same way: guessing can earn partial credit, but admitting "I don't know" always scores zero under standard accuracy benchmarks. So models learn to guess.

The research also measured this directly. Newsweek reported that in OpenAI's own tests, a newer model (GPT-5-based) had a 52% abstention rate (saying it wasn't sure) with a 26% error rate, while an older model (o4-mini) abstained only 1% of the time but was wrong 75% of the time. The older model looked more "helpful" because it rarely refused to answer, and that's exactly the problem: it was wrong three times out of four when it did.

OpenAI's proposed fix, at the model-training level, is to redesign how models are scored so that an honest "I don't know" is rewarded instead of punished. That's a change to how AI companies build and test models generally. It doesn't directly fix a single store's chatbot, but it explains the mechanism behind every wrong answer you've seen one give.

Why this matters more for a store chatbot than a general one

A general-purpose chatbot getting a trivia question wrong is a minor annoyance. A store chatbot getting a policy or product question wrong goes out with your brand attached, to a real customer who will expect you to honor what it told them. A wrong answer about a return window, an ingredient, or a shipping cost can cost you a sale, a refund you didn't plan on, or a customer you can't get back. See why shoppers hate store chatbots for what that looks like from the shopper's side.

What actually reduces wrong answers in a store chatbot

You can't retrain the underlying model yourself, but you control the setup around it, and that's most of what causes a wrong answer in practice:

• Restrict it to your own content. A chatbot that can only answer from your website's actual pages has far fewer gaps to fill with a guess than one that's allowed to answer from its general training data. If a shopper asks something your pages don't cover, there's nothing to read, and a well-built bot says so instead of inventing an answer.
• Make "I'm not sure" an explicit, allowed answer, not something the bot has to work around. This is the exact fix OpenAI's research points to: if the system only rewards a confident-sounding answer, it'll keep producing one, right or wrong.
• Keep the source pages current. A bot answering from a shipping policy you changed three months ago but never updated on the page isn't hallucinating; it's reading stale information correctly. See how to train an AI chatbot on your Shopify content for keeping the underlying pages accurate.
• Check its unanswered questions regularly. A log of what it couldn't answer is also a log of where your content has gaps, which is where guesses are most likely to creep in.

How Chatbait handles this

Chatbait's AI agent answers only from the store's own pages, and when the answer isn't there, it's built to say "I'm not sure" and point to the owner's contact details rather than guess. That matches the fix in the research above: narrowing what it's allowed to answer from, and treating "I don't know" as a normal response. It won't catch every edge case; if a page is vague or wrong, the AI agent will repeat that inaccurately worded page back with confidence, because from its side, that's what your site says.

1. 1

   Reads your pages

   Products, FAQ, shipping, returns, about.

2. 2

   A shopper asks

   “Do you ship to Ireland?”

3. 3

   Finds it on your site

   Answers in your words, any hour.

4. 4

   Not on your site?

   Says so, and gives your contact details.

Frequently asked questions

Why do AI chatbots make up answers instead of saying they don't know?

Because the way most language models are trained and scored rewards a guess over an admission of uncertainty. OpenAI's September 2025 research found models are evaluated like a multiple-choice test, where guessing scores better on average than leaving a blank, so models learn to guess confidently even when they shouldn't.

Can a store stop its chatbot from hallucinating completely?

Not completely, but you can cut it down a lot by restricting the bot to your own website's content and making sure "I'm not sure" is an allowed answer rather than something the bot avoids. A bot with fewer gaps to fill, and permission to admit it doesn't know, guesses far less often.

Is a chatbot that refuses to answer sometimes better than one that always answers?

Usually, yes, for a store. OpenAI's own data found a model that abstained 52% of the time was wrong only 26% of the time it did answer, while a model that almost never abstained was wrong 75% of the time. A customer-facing bot that occasionally says "I'm not sure, here's how to reach us" is more trustworthy than one that always sounds confident.

Does restricting a chatbot to a store's own pages fully prevent wrong answers?

No. If the page itself is vague, outdated, or wrong, the chatbot will repeat that inaccuracy with the same confidence. Restricting the bot's source material reduces invented answers, but it doesn't fix bad source material; that still needs a human to catch and correct.