AI chatbot checklist for small businesses

An AI chatbot can answer common questions at any hour, take enquiries while your team is busy and point visitors to the right page. It can also give wrong answers with complete confidence, collect personal data you did not plan for and annoy customers who wanted a person. The difference usually comes down to planning. Use this checklist before you build or buy a chatbot for your business.

What should your chatbot do, and what should it not do?

Start with one or two clear jobs. Good first jobs for a small business are:

• answering questions about products, services, opening hours, delivery and returns;
• collecting enquiry details and passing them to your team;
• booking a call or an appointment;
• finding the right page on your website.

Write down what the chatbot must not do as well. For most businesses that list includes giving legal, medical or financial advice, promising prices or delivery dates it cannot check, and discussing topics that have nothing to do with your business. These limits become instructions for the chatbot and test cases later.

Which content will it answer from?

A general-purpose AI model knows a lot about the world and nothing about your business. To answer correctly, a business chatbot needs your own content: service pages, FAQs, policies, product data and opening hours. The usual approach is called retrieval-augmented generation (RAG): when a question comes in, the system finds the most relevant passages from your content and asks the model to answer from those passages only.

Before you build, check your content:

• Is it up to date? A chatbot repeats old information as confidently as new information.
• Is it complete? If your returns policy is only in someone's head, the chatbot cannot know it.
• Does it contradict itself? Two pages with different delivery times will produce inconsistent answers.
• Who will keep it current, and how will changes reach the chatbot?

Our page on RAG AI agents explains this approach in more detail.

When should the chatbot hand over to a person?

A chatbot should know when to stop. Plan the hand-off before launch:

• When it does not know. If the answer is not in your content, it should say so and offer to pass the question on, not guess.
• When the customer asks. "Can I talk to someone?" should always work.
• When the topic is sensitive. Complaints, refunds and anything involving health or money are often better handled by people.
• Outside your hours. Decide what the chatbot promises when nobody is available: a call back the next working day, an email reply, or a booking link.

Make sure every hand-off reaches a real inbox or dashboard that someone checks. A chatbot that collects enquiries nobody reads is worse than a contact form.

How will it handle personal data?

Customers will type names, phone numbers, email addresses and sometimes much more sensitive details into a chat box. Decide in advance:

• what the chatbot asks for, and why you need it;
• where conversations are stored, for how long and who can read them;
• which AI provider processes the messages, in which country, and whether that provider may use the data to train its models;
• how a customer can ask you to delete their conversation.

Update your privacy policy to describe the chatbot. Privacy laws differ by country, so check the rules where your customers live, and tell people clearly that they are talking to an AI system. In the European Union, for example, the AI Act includes a transparency duty to inform people when they are interacting with an AI system.

Who is responsible for what it says?

You are. In 2024 a Canadian tribunal decided that Air Canada was responsible for incorrect information its website chatbot gave a customer about a fare policy, and rejected the argument that the chatbot was a separate entity. Treat chatbot answers like any other content on your website: if it says something, your business has said it. That is why the content checks, the limits and the hand-off rules above matter.

Which model and channels should you choose?

Most business chatbots use a model from one of the large providers, such as OpenAI, Anthropic or Google, or an open-weight model that can run on your own servers. The right choice depends on answer quality in your language, speed, data-handling terms and running costs, which are usually charged by usage. You do not need to decide this alone: a developer should be able to test two or three models on your real questions and show you the results side by side.

Think about where customers already talk to you. A chat window on your website is the usual start. Many businesses also connect the same assistant to WhatsApp through the WhatsApp Business Platform, or to their help desk.

How do you test it before launch?

Collect 50 to 100 real questions from your emails, calls and messages, including awkward ones. Then check:

• Does it answer correctly from your content, and link to the right page?
• Does it refuse politely when the question is outside its limits?
• Does it hand over when asked, and does the enquiry arrive?
• Does it behave when someone tries to make it ignore its instructions?
• Does it work on a phone, with a keyboard and with a screen reader?

Fix the content and the instructions, then test again. Keep the question list: it becomes your regression test every time you change the chatbot.

What should you watch after launch?

Read a sample of conversations every week for the first month. Track a few simple numbers: how many conversations end with an answer, how many need a person, which questions it could not answer, and how many enquiries or bookings it produced. The unanswered questions are the most useful list you will get: each one points to a gap in your website content as well as in the chatbot.

If you want a chatbot planned and built this way, see our AI chatbot development service or our wider AI solutions. We are also happy to review a plan you already have: get in touch.