Short answer: start automating customer service with the repetitive questions: opening hours, prices, order status, delivery and returns. A bot or an AI agent answers them from a knowledge base you have approved, while complaints, custom offers and unclear cases are handed to a person together with the full conversation history. Start with one channel: website chat, email or WhatsApp.
An example: a customer on the website asks "Where is my order?" → the bot asks for the order number → checks the status in the online store system → replies with a parcel tracking link. If the order cannot be found or the customer is unhappy, the conversation is handed to an employee with the context, by email or Slack. I build website chatbots as a service (AI chatbots for business), and solutions that take actions in your systems themselves as an AI agent (AI agent development).
- 1The customer asks in the website chatChatbot
- 2The bot asks for the order number
- 3Checks the statusOnline store system
- 4Replies with a parcel tracking link
- 5Not found or the customer is unhappy – handed to a personEmail · SlackTogether with the full conversation history.
But automating customer service also carries a risk: if the AI answers inaccurately or sounds robotic, it can hurt the customer experience more than a slow but genuine human reply. That is why the rollout process matters.
Which customer questions can be automated?
In many companies a large share of customer questions repeat: opening hours, addresses, prices, delivery times, warranty terms, return policy. These questions are ideal for automation.
Questions worth automating: basic information about services and products, status checks (order status, invoice status), solving simple problems (how to use a product, how to set it up), booking and canceling appointments, and requests for documents or instructions.
More complex cases (complaints, custom pricing, escalated technical questions) should always go to a person. The AI has to know its limits and hand over the conversation smoothly when a situation is beyond what it can handle.
What types of AI customer service solutions are there?
Rule-based chatbots: they work from a predefined tree, "if they ask X → answer Y". Fast, reliable and inexpensive. The downside: they cannot understand unexpected questions or unusual ways of writing.
AI chatbots (NLP): they use natural language processing (for example, Claude, GPT-4, Llama). They understand questions written freely, can answer more complex questions and learn from conversations. They suit businesses where customer questions are varied and unpredictable.
Hybrid solutions: usually the recommended option. The AI handles standard questions, and complex or sensitive ones are handed to a person. This is the best balance between efficiency and service quality.
How to roll out AI customer service step by step
Step one: collect and organize the most common questions. Go through the last 3 months of emails, chats and WhatsApp messages and identify the 20–30 questions that come up most often. This will be the basis of the AI's "knowledge base".
Step two: decide which questions should go to a person: complaints, complex situations, high-value customers, emotionally sensitive conversations. Clear escalation logic is essential.
Step three: pick the right tool: a rule-based system for simple questions, an AI bot for more complex ones. Start with one channel (for example, website chat), test it, improve it, and only then expand.
Step four: monitor and improve. The first month is a learning period. Review the conversations where the AI made mistakes or the customer was unhappy, and improve the answers.
- 1Collect the 20–30 most common questionsFrom the last 3 months of emails and chats.
- 2Decide what goes to a personComplaints, sensitive and high-value cases.
- 3Launch in one channelWebsite chat
- 4Review and fix mistakes during the first month
Does AI customer service work in Lithuanian?
Lithuanian is a specific challenge for AI replies. Large language models (Claude, GPT-4) understand and write Lithuanian well, but the output needs extra checking, especially with technical or specialized terms.
A practical tip: write specific reply templates in Lithuanian and use AI to personalize the templates (inserting the customer's name, updating a date or status), not to generate free text. That way you avoid language errors and keep a consistent tone.
An alternative: use AI for classification (identifying the type of question) and replies prepared by a person for each category. It is less "shiny", but a more reliable solution for many Lithuanian businesses.
How much does AI customer service cost, and what can you expect?
A simple FAQ bot for a website or WhatsApp: €450–600 to set up, from €150/month for support (optional). An AI chatbot with a knowledge base and escalation logic: €800–1,800 to set up, €100–200/month.
Work out the payback from how many hours a day your team spends on the same answers today, and what share of those questions the bot could answer without a person.
It is important not to have unrealistic expectations: AI does not solve every problem. The best result is AI as help for the service team, not a full replacement for it. Then the customer experience improves, and the team's time is freed up for more complex cases.