AI agents & automation
Why AI Agents Make Things Up (and How to Stop Yours)
AI models guess when they lack information; that is how a bot invents a price or a policy. Why it happens, and how information, rules, and testing prevent it.
Ask any business owner what stops them from putting AI in front of customers and you will hear the same story: "I tried a bot and it invented a price," or "it promised a delivery date we could never meet." The behavior has a technical name, hallucination, but you do not need the jargon to recognize it. It is the moment an AI answers a question it does not actually know the answer to, and does it with total confidence.
The quick answer: AI language models are built to produce the most plausible-sounding response, and by default they would rather produce a plausible guess than say "I do not know." When a bot has no access to your real prices, policies, and stock, plausible guessing is all it can do. The fix is not a smarter model, it is a better setup: ground the agent in your real business information, give it firm rules, let it escalate instead of improvising, and verify its answers before and after launch.
Why it happens
A language model works by predicting what text should come next, based on patterns from everything it has read. That makes it remarkably good at sounding right. It also means the model has no built-in sense of "I have no idea," because there is always some plausible next sentence to produce. Asked "how much does shipping to Monterrey cost," a model with no access to your rates will not go silent. It will produce a number that sounds like a shipping cost, because producing likely-sounding text is precisely what it is built to do.
When your agent is most likely to invent
Made-up answers cluster in predictable places. When the information is missing: the customer asks about a product, price, or policy that nobody gave the agent. When the information is stale: prices changed, the promotion ended, but the agent still has last month's data. When the question is out of scope: something you do not sell or a topic (legal, medical) it should never touch. And when the question is ambiguous and the agent guesses your intent instead of asking. Notice what these have in common: none of them are fixed by making the AI "smarter." They are fixed by information, rules, and honest escape routes.
How to prevent it
Ground it in your real information. The single biggest lever. An agent that answers from your actual catalog, prices, hours, and policies has no need to invent them. Whatever tool you use, the question to ask is: where do its answers come from?
Give it firm rules and an exit. Define what it must never say and what it should do when unsure. "I do not have that information, let me connect you with the team" is a perfectly good answer, and a reliable agent must be allowed to give it. Bots invent most when they are implicitly required to always have an answer.
Hand off instead of improvising. Out-of-scope and sensitive questions should route to a person, cleanly, without the customer repeating themselves. That single behavior removes most of the high-stakes ways an agent can be confidently wrong.
Verify before and after launch. You find invented answers by looking for them: run your real customer questions through the agent before it goes live, including the ones it should not answer, and keep watching after launch as your prices and policies change. Here is how to test a WhatsApp AI agent before you launch it, and the bigger picture in how to have a reliable AI agent on WhatsApp.
Common questions
Can you stop an AI from ever making things up? No honest vendor will promise zero. What you can do is make invention rare and catchable: ground the agent in your real information, give it rules and an escape route, and verify its answers before and after launch, so the rare miss becomes a clean handoff or a caught test failure instead of a confident wrong answer to a customer.
Is a bot that invents answers broken? No, and that is the uncomfortable part: it is doing exactly what a language model does by default. Producing plausible text is the design. That is why the fix lives in the setup around the model (information, rules, handoff, verification), not in waiting for a model that never guesses.
How do I know if my current bot is inventing answers? Test it against questions you know the true answer to, especially ones whose answer is not in whatever information it was given, and see what comes back. If you cannot see or test what your bot knows, that opacity is itself the warning sign. Chatbot vs AI agent explains the kinds of automation and what to expect from each.
Ciarem is an AI agent for WhatsApp, Instagram, and web chat that answers from your real business information and lets you check it is answering correctly before you trust it with customers. Meet the WhatsApp AI agent.