Chatbot

AI Glossary

In plain English: A chatbot is a program that talks with you through text — older ones follow strict rules, newer ones use AI to understand and respond more naturally.

What it really means

When I say “chatbot,” I mean any software that lets you type a question or statement and get a text reply back. It’s that simple. The magic — or lack of it — depends on what’s under the hood.

There are two main types I’ve worked with:

• Rule-based chatbots. These follow a script. You type “hours,” it shows store hours. You type “pricing,” it shows pricing. If you type something unexpected, it usually says “I didn’t understand that.” These are cheap, predictable, and fine for simple tasks.
• AI-powered chatbots. These use large language models (LLMs) — the same tech behind ChatGPT. They can handle open-ended questions, rephrase answers, and even hold a conversation. They’re more flexible, but they can also make things up or ramble if not set up carefully.

Most businesses I talk to in Orlando are running the first type without realizing there’s a second, better option available now.

Where it shows up

You’ve almost certainly used a chatbot in the last week. That little chat bubble in the bottom corner of a website? That’s a chatbot. The automated text you get from your bank when you ask about a transaction? Also a chatbot.

In Central Florida, I see them most often on:

• Service business websites. An HVAC company in Maitland might use one to book emergency repair calls after hours.
• Dental and medical practices. A Winter Park dentist’s chatbot can handle appointment scheduling and insurance questions.
• Restaurant sites. A Lake Nona eatery might use one to take reservations or answer menu questions.
• E-commerce stores. “Where’s my order?” is the most common question, and a chatbot can answer it instantly.

They also show up inside apps — think of the support chat in your banking app or the virtual assistant in a car rental site.

Common SMB use cases

For small and mid-market businesses, chatbots aren’t about replacing people. They’re about handling the repetitive stuff so your team can focus on work that actually needs a human. Here’s what I’ve seen work well:

• After-hours lead capture. A pool service in Clermont can’t answer the phone at 9 PM. A chatbot can take down the customer’s info, describe the problem, and schedule a callback for morning.
• Appointment booking. A law firm in downtown Orlando can let clients book consultations through a chatbot without tying up a paralegal.
• FAQ deflection. “What are your hours?” “Do you service my area?” “How much does an oil change cost?” — an auto shop in Sanford can answer these instantly, every time.
• Order status. A local retailer can let customers check order status without calling or emailing.
• Internal FAQ. Some businesses use chatbots on their internal Slack or Teams to answer employee questions about HR policies or IT support.

The ROI is usually time saved. I’ve seen small teams reclaim 10–15 hours a week just from chatbot-handled questions.

Pitfalls (what gets oversold)

I’ve had more than one client come to me after buying a chatbot that promised the moon and delivered a headache. Here’s what to watch for:

• “It will replace your support team.” No, it won’t. A good chatbot handles the first 80% of simple questions. The remaining 20% — angry customers, complex issues, nuanced requests — still needs a human. Anyone who says otherwise is selling something.
• “It understands everything.” AI chatbots are better than rule-based ones, but they still get confused. They can misinterpret sarcasm, miss context, or confidently give wrong answers. You need to monitor and tune them.
• “Set it and forget it.” Chatbots need maintenance. Business hours change, products get discontinued, new FAQs pop up. A chatbot that’s not updated becomes a liability.
• “It’s cheap and easy.” A simple rule-based chatbot is cheap. A well-built AI chatbot that actually helps customers takes planning, testing, and ongoing tweaking. The upfront cost is just the beginning.

I’ve seen a Winter Park dental practice waste six months on a chatbot that couldn’t handle “I have a toothache, can you fit me in today?” — because the chatbot only understood “schedule appointment.” The gap between what’s sold and what works is real.

Related terms

• Large Language Model (LLM): The AI engine that powers modern chatbots. Think of it as the brain — the chatbot is just the interface.
• Conversational AI: A broader term covering any AI that can hold a conversation, including voice assistants like Siri or Alexa.
• Prompt engineering: The skill of writing instructions for an AI chatbot so it gives useful, accurate answers. It’s more art than science.
• Intent recognition: What the chatbot does when it figures out what you actually want — like recognizing “I need help with my bill” is about billing, not technical support.
• Knowledge base: The collection of documents, FAQs, and data the chatbot pulls from to answer questions. A chatbot is only as good as its knowledge base.