What is an AI customer agent, and how to choose one?
An AI that truly works like a customer agent on a website; it understands the question, finds the answer from your knowledge, and performs actions on the site when needed. This guide explains the difference and what to look for when choosing.
The term “AI customer service representative” has been used in recent years for very different products: chatbots selecting from pre-written responses, tools summarising FAQ pages, or language models answering customers’ questions in free-text format. This guide explains what an AI truly acting as a customer representative on a website must be able to do and what to look for during setup.
Difference between chatbot and customer representative
A classic chatbot follows a predefined flow: a visitor clicking the 'Where is my order?' button is given a link to the order tracking page. Any question that falls outside the flow either remains unanswered or ends with the phrase 'I am connecting you to an agent.' The problem with this approach is that the visitor must force their question into the template defined by the site.
If it were a human customer representative, they would do three things simultaneously: understand the question, find the answer from the company's knowledge base, and perform an action if necessary (add the product to the cart, open an appointment, query the shipment). For an AI to be considered a 'customer representative', it must be able to do all three. A system that only talks but cannot act will ultimately redirect the visitor to a page or a phone number again.
Where should the source of the answer be?
The general knowledge of a language model does not know your shipping duration, return conditions, or promotions. An AI working as a customer representative should base its answers on the sources you provide. These sources generally fall into three categories:
- Knowledge base: frequently asked questions and policy texts (delivery, returns, warranty, opening hours).
- Catalogue: products, prices, stock, product pages; in large sites, directly the store database.
- Current page: the page of the product or service the visitor is currently viewing.
An answer with an unknown source is risky, no matter how fluent it is. Therefore, in a good system, the source on which each answer is based should be visible afterwards.
The catalogue should not be fed wholesale to the model
A catalogue with hundreds of thousands of products is not text that a language model can read in one go; even if it could, doing this for every question would be both slow and expensive. The correct approach is for the AI to first clarify what it is looking for, then search the catalogue, and write the answer using only the few products found. The price and image shown on product cards should also be values coming directly from the catalogue, not written by the AI; otherwise, there is a risk of stating incorrect prices.
Ability to act but knowing its limits
An AI acting on your site should only be able to perform actions you have permitted. To achieve this, the site defines possible actions (adding to cart, opening an appointment form, applying a coupon) with their names and parameters; the AI cannot go beyond these. Important steps such as placing an order or submitting a form should wait for the visitor's explicit consent.
When should it hand over to a human?
Even the best AI agent shouldn't answer every question. Bulk purchase discounts, changing the order address, complaints, or uncertain technical queries are your team's responsibility. Handover has two conditions: your team must be able to pick up the conversation where it left off, and the AI must fall silent upon handover. If no one is online, the visitor's contact details should be collected and passed to the team.
What to check during setup
Check the source of answers, catalog import, what tasks the AI can perform, and the team's handover process.
- Which sources do the answers rely on, and can you manage these sources?
- How is the catalog imported; how is response speed maintained for large catalogs?
- What tasks can the AI perform on your site, and how are these tasks restricted?
- What is displayed on the payment page and in form fields?
- How does your team monitor and take over conversations?
- Can you see how each answer was generated?
Job description: telling the agent what to do
When hiring a human agent, you don't just give them the product catalogue; you also explain their role: which questions to answer, what information to collect, and when the task is considered complete. The same applies to an AI agent. In a clinic, the task is 'booking an appointment', with the condition being that the appointment is written into the calendar. On a spare parts site, the task is 'finding the compatible part', which requires clarifying the vehicle first. An AI without a defined task gives generic answers to every query; one with a defined task guides the conversation toward a result.
Industry templates shorten the start by providing these tasks ready-made. A template is a starting point: you can change the questions, information to collect, and end conditions according to your own workflow.
Tone and brand voice
How the agent speaks is as important as what it says. If an e-commerce site's agent speaks formally while the site uses an informal tone, visitors will find it strange; conversely, a law firm's agent might seem untrustworthy if too informal. In a good system, tone is a setting applied consistently across all conversations. The greeting message is the first example of this tone: the first sentence the visitor sees when opening the window sets the tone of the conversation.
Cost and control
AI usage incurs a cost, which increases with the number of conversations. Therefore, usage must be visible and limitable: daily and weekly limits, amounts spendable per visitor, reusing previous answers for repeated queries. There should also be protection against out-of-topic messages or those attempting to steer the system; otherwise, a single malicious visitor could consume the entire monthly allowance.
What to focus on in the first week?
The first week of setup is when the agent meets real visitor questions. Reading conversations this week shows which questions went unanswered, which answers were too long, and which topics were handed over to the team. Every unanswered question is an item to add to the knowledge base; every unnecessary handover is a point to clarify in the job description. Regular maintenance over a few weeks significantly increases the percentage of questions the agent can answer.
How SmartOperator solves this
SmartOperator bases its answers on the knowledge base, catalogue, store database, and the page the visitor is on; the steps for each answer are visible in the dashboard.
- Sources: knowledge base, catalogue, store database, and the page the visitor is on.
- Site actions: actions defined by the site; important ones require visitor consent.
- Payment page rule: no reading or action is performed on the payment page.
- Live handover: your team takes over with a single click, and the AI falls silent.
- AI trace: the steps for each answer are visible in the dashboard.