In today’s era of technological advancements, it’s highly likely that you've interacted with a chatbot instead of a human customer support agent.

Whether on an e-commerce platform or a service provider’s website, this technological revolution has made it essential for many businesses to integrate a chatbot.

A chatbot trained on limited data must answer queries from a source that even the largest and most accurate predictive models can't predict: the human brain.

This raises a crucial question: are chatbots, outside of just following trends and hype, truly reliable with a company’s critical information? If a chatbot were to misquote something, it could be fatal to an organization’s reputation.

If this question gives you pause, let’s delve deeper into the essential stuff. There are countless chatbot options available, from no/low-code solutions to fully custom-coded chatbots.

Imagine a company integrates a chatbot on its website, thinking it will modernize the site and show they're keeping up with the latest tech shifts. The next thing they realize is that the chatbot has interacted with potential clients and misquoted services, project timelines, and even pricing. A service supposedly offered for $700 is now bound to a $399 price because the "customer support" chatbot said otherwise.

. Denying this and not taking responsibility will only result in the company losing credibility as a reputable organization.

. Do all categories of chatbots have these issues?

A company might use a no-code platform to create a chatbot to quickly integrate on its portfolio website. The idea would be for it to answer basic FAQs, with its knowledge limited to certain questions. Any questions beyond its scope would be redirected to the official support email. This seems like a sound strategy.

However, as the company moves forward with its creation, it might begin to realize, "How many questions can we actually cover?" If the company only uses questions they come up with, and a user tweaks how they ask them, the chatbot’s answers will differ. The solution, they might think, is to use AI to handle queries.

But is this really the solution or an additional concern? AI could start to give answers that go beyond the chatbot’s intended scope and misquote information from its search data.

No matter how much information is given to the chatbot, it always seems to fall short of the questions it’s asked. Balancing the right amount of information to be given to the chatbot without using the AI's self-provided data can be a struggle.

The chatbot might start feeling more like an FAQ in a text box with buttons suggesting what the user should ask rather than a reliable support for the end user's queries.

So the question still remains: Do you trust your clients with your AI bot?

The Path Forward

. Your Data Is Its Brain: The bot is only as smart as the data you give it. If your information is limited, its answers will be, too.

. Humans Are Unpredictable: You can't predict every question a person will ask. A bot with a fixed list of answers will always fall short.

. Mistakes Cost You: A single incorrect price or service detail from your bot can damage your reputation and cost you a client.

. AI Needs Supervision: AI can go "off-script." Without you watching, it might say something harmful or irrelevant.

. A Bot Isn't a Person: Use it to handle simple questions, but for anything complex or critical, a human touch is still essential.

References

. Training Data is Everything

Medium (2023). "How to Create an AI Chatbot: A Comprehensive Guide to Building Intelligent Conversational Agents" [1]

. You Can't Predict Human Questions

Arxiv (2025). "A Human-Like AI Communicates with Uncertainty." Communications of the ACM, 65(9), 8–10. [2]

. Mistakes Cost You

OECD Publishing. (2024)." Assessing Potential Future Artificial Intelligence Risks, Benefits And Policy Imperatives" [3]

. AI Needs Supervision

PubMed Central. (2023). "AI chatbots and (mis)information in public health: impact on vulnerable communities." [4]

. A Bot Isn't a Person

MIT Sloan. (2025). "When humans and AI work best together — and when each is better alone" [5]