Do's and don'ts when creating chatbots

Last updated: 25.09.2025 10:00

Chatbots are now part of everyday life in many contact centers. They can relieve the team of customer inquiries, speed up processes and ensure round-the-clock service. But experience shows: Success depends not only on the technology, but above all on how chatbots are planned, implemented and further developed.

Our AI experts have summarized their experiences and named the most important do's and don'ts for working with chatbots.

Don'ts - mistakes you should avoid

1. not getting started

The biggest mistake is not even starting out of fear or uncertainty. If you hesitate, you will lose touch with the competition while other companies are already gaining experience and optimizing their systems.

2. excessive humanization

A chatbot may sound friendly and pleasant, but it is not human. Customers feel deceived if they engage in small talk and only realize later that they are talking to an AI. Better: Focus clearly on solving problems and make it clear that it is an AI system.

3. "ChatGPT only" thinking

Relying exclusively on one model or one provider is risky. The variety of models is growing every week, and large language models are not the best solution for all tasks. Other AI systems, for example for assistance functions, can sometimes make more sense.

4. overambitious automation

Trying to automate everything at once can quickly lead to excessive demands. If you go too far, you run the risk of overwhelming the database, processes or user acceptance.

Do's - success factors for chatbots

1. define guard rails

A system whose responses are neither checked nor regulated harbors risks. In the worst case, "hallucinations" of AI models can lead to false information or even damage to the company's image. Guardrails, i.e. content-related guard rails, are therefore mandatory.

2. select suitable use cases

Not every task is suitable for automation. Start where the benefits are great and the process is clearly structured, for example with standard inquiries or repetitive service cases. After all, chatbots are not all-rounders. They are successful where they take on clearly defined tasks, e.g. address changes, order status queries or FAQs. Companies should define exactly which use cases are to be automated and which belong on the agent desk.

3. check the database

A chatbot is only as good as the database it accesses. Check whether the relevant data is available, accessible and of high quality. If it is missing, a basis must first be created.

4 Think big, start small

Have a vision of where you want AI to take your contact center, but proceed in small steps. This allows teams to gain experience, correct mistakes and build trust in the technology.

5. start internally

Test chatbots in internal applications first, for example to support employees. Error tolerance is higher there and feedback is more direct. Only when the systems are stable is it worth using them in customer communication.

6 Gather experience & develop further

A chatbot project is never "finished". Technologies, models and expectations are developing rapidly. Systems must be continuously adapted and optimized in order to remain relevant.

Conclusion: chatbots need strategy and courage

The introduction of chatbots is not an end in itself. It is a strategic decision that affects customer experience, efficiency and competitiveness in equal measure. The most important insight: don't wait, get started - but with clear guidelines, realistic expectations and a step-by-step approach. This results in chatbots that not only save costs, but also create real added value for customers and employees.