Chatbots: Simply Explained

What are Chatbots?

A chatbot is software designed to communicate with people via text-based or voice-based interfaces, understand their input, and respond to it. A chatbot simulates a conversation with a user, handles dialogues—for example, in a question-and-answer format—and can provide automated responses. Technically speaking, a chatbot is software that uses rules or algorithms (e.g., natural language processing) to take a user's text input and generate appropriate responses as output.

Well-known chatbots include ChatGPT (OpenAI), Gemini (Google), Copilot (Microsoft), Claude AI (Anthropic), and Le Chat (Mistral).

Chatbots and Artificial Intelligence

The connection between chatbots and artificial intelligence lies in the fact that many modern chatbots use AI techniques – in particular natural language processing (NLP), machine learning, and sometimes generative models – to enable more natural, flexible, and, above all, context-aware dialogues.

Not all chatbots are based on artificial intelligence—there are also simple, rule-based systems that work without machine learning. However, what all chatbots have in common is that they were developed to interact with users. They differ in their degree of “intelligence”: some work purely on a rule-based basis with predefined decision trees, while AI-supported variants can understand unstructured text, learn from experience, take context into account, and in some cases even generate their own content.

Types of Chatbots

The various chatbots can be distinguished based on several criteria. The following list shows the main types and categories of chatbots:

• Rule-based chatbots: This type of chatbot works with predefined rules, decision trees, or scripts. The dialogue flow is highly structured, with the chatbot recognizing certain keywords or phrases and responding with the assigned answers. It is limited in that it cannot learn new patterns or respond flexibly to unusual inputs.
• AI-based chatbots: These chatbots use technologies such as natural language processing, machine learning, and neural networks. They are able to understand free and unstructured text inputs, recognize the intent behind a query, and formulate appropriate responses. Through continuous training, they improve over time and can respond to new formulations with increasing flexibility.
• Hybrid-based chatbots: Hybrid chatbots combine a rule-based and AI-based approach. In standardized cases, the bot relies on rules and decision trees, but in more complex dialogs or in the event of deviations, it activates AI modules to respond flexibly. This combines reliability for standard questions with flexibility for unforeseen queries.
• Informative chatbots: Their main purpose is to provide information, answer questions, and offer assistance, e.g., in FAQs or knowledge bases. They tend to be passive and reactive in their programmed nature.
• Executive chatbots: These bots (also known as transactional or action bots) go beyond simply providing information and perform actions such as bookings, orders, appointments, account queries, or automatic processes. In order to be able to carry out these actions, they are integrated into the target systems.

Overview of Popular Chatbots

How do Chatbots work?

Chatbots generally follow a typical sequence when performing their actions:

First, the user enters a request—either via text or voice. The bot receives this input and converts it into a machine-readable form through a process known as parsing, for example through tokenization, normalization, or the removal of stop words. It then analyzes the request to understand what the user wants (the so-called intent or intention) and identifies relevant keywords or entities such as “booking,” “flight,” “date,” or “location.”

AI-based chatbots often use an NLP (natural language processing) module that analyzes the syntactic and semantic structures of language. A dialog manager then decides how to continue the conversation: which response or follow-up question is appropriate, whether further contextual information is needed, or whether the next step should be initiated. The bot controls the course of the conversation using rules, state machines, or AI models.

Depending on the system, the chatbot then either provides a predefined response (in rule-based systems) or a newly generated response (in AI-based systems). If the bot can also perform actions – such as initiating a booking or retrieving data – this is done via interfaces to backend systems or APIs. Advanced, AI-powered chatbots can also learn from previous conversations and user feedback. They adapt their models, recognize new phrases or intents, and optimize their responses. This learning can be supervised or unsupervised, for example, using classifiers, neural networks, or reinforcement learning.

Some systems also retain the conversation context across multiple interactions. This allows them to remember what was discussed previously, make references back to it, and ask specific follow-up questions. To do this, they manage the dialogue history in so-called sessions or via context variables that store the current status of the conversation.

Benefits and Challenges

Benefits of Chatbots

• Scalability and 24/7 service: Chatbots can respond to multiple inquiries around the clock without the need for a proportional increase in human resources.
• Fast response times and increased efficiency: Users receive immediate answers to standard questions, eliminating waiting times. This reduces the workload on service teams and cuts costs.
• Lead generation and increased sales: Chatbots can actively accompany visitors, ask qualifying questions, make recommendations, or lead them to a specific conclusion.
• Personalization and user retention: With the right data, chatbots can make individual recommendations or adapt to the user profile.
• Automation of recurring processes: Many routine tasks such as scheduling appointments, processing forms, or simple support requests can be handled automatically.

Challenges with Chatbots

• Data protection & security: When personal data is transmitted in conversations, data protection regulations (e.g., GDPR) must be complied with. Storing, processing, and securing conversations can be challenging.
• Costs and development effort: Implementing intelligent chatbots (especially when using AI) can be costly—both in terms of technology and training and maintenance.
• Limited reliability or misinterpretations: Chatbots can misinterpret inputs, lead to dead ends, or provide inappropriate responses (e.g., when the request is outside the scope of what they have learned).
• Lack of empathy and human understanding: Bots often reach their limits, especially when it comes to sensitive or emotional topics.
• Maintenance and updating: Content, responses, and models must be regularly maintained and improved, especially when product information, offers, or processes change.

Areas of Application

Chatbots are now used in a wide range of industries and areas of application:

• In customer service, chatbots usually handle the initial contact, answer frequently asked questions, and forward more complex issues to service teams. They reduce the workload on employees, cut waiting times, and enable round-the-clock service.
• In retail and e-commerce, chatbots act as informational or executive systems. They help customers search for products, provide information about delivery times or returns, and accompany them throughout the entire purchasing process. In addition, they provide personalized recommendations or present additional offers, which improves the shopping experience and increases the conversion rate—i.e., the likelihood of a purchase.
• In banking and finance, too, more and more companies are relying on AI-supported or hybrid chatbots. These answer questions about account balances, transfers, or credit offers and provide support for everyday banking transactions. Some systems recognize suspicious transactions or handle simple consultations, thereby contributing to greater security and efficiency in customer service.
• Chatbots are becoming increasingly important in healthcare, especially in the field of mental health. They offer low-threshold support, record symptoms, give simple recommendations, or refer users to appropriate specialist services. Although they are no substitute for therapy, they enable quick, anonymous help and at the same time relieve the burden on medical staff – especially for people who are reluctant to seek professional help directly.
• In recruitment and human resources management, chatbots are primarily used to communicate with applicants. They answer questions about job vacancies, company benefits, or application processes and coordinate interview appointments. Some systems even perform an initial pre-selection of candidates based on predefined criteria. This makes recruiting more efficient, applicants receive feedback more quickly, and HR departments are freed from routine tasks.
• Another key area is marketing. Here, chatbots are used to generate leads, actively address visitors to websites, or guide them through the purchasing process. They can conduct surveys, make product recommendations, or place targeted personalized advertising messages. In this way, they increase the interaction rate, promote customer loyalty, and contribute to increased sales.
• Chatbots are now also widely used in private communication, for example via messenger services such as WhatsApp or Telegram. These systems – often simple, but sometimes also AI-supported – take on small everyday tasks: they remind users of appointments, provide weather reports, send news updates, or organize calendars. Their biggest advantage lies in the convenience and time savings achieved through the automation of recurring tasks.

Chatbots are also used in many other areas. In education, they serve as digital learning assistants, explain learning content, ask quiz questions, or help with exam preparation. In the tourism industry, they facilitate travel planning and provide information on sights or booking options. Even in public administration, chatbots are increasingly being used to provide citizens with quick and understandable information about forms, applications, and government services.

Conclusion

In recent years, chatbots have developed into versatile digital assistants that simplify communication and accelerate processes in almost all industries. Through the use of artificial intelligence, they can not only provide static responses, but also increasingly conduct human-like dialogues and take on complex tasks. Despite all the advantages, such as time savings, cost efficiency, and constant availability, challenges remain, particularly in terms of data protection, the accuracy of responses, and maintaining human empathy. Nevertheless, it is foreseeable that chatbots will play an even more important role in the future, both in private and professional environments.